#machine-learning

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floral iris
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"The Writer's Workbench (wwb) was a software package developed for the Unix operating system by Lorinda Cherry and Nina McDonald of Bell Labs."

spring pilot
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Oh, cool!

floral iris
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I've been reading through a pdf of Doug McIlroy's "A Research UNIX Reader" and her name has popped up pretty often. He seems quite impressed with her work on dc.

spring pilot
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That would be interesting....

floral iris
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(dc - an arbitrary precision calculator -- not trying to be obscure)

spring pilot
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Not "bc" by any chance?

weak oyster
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dc rox

floral iris
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He does credit her ("Morris and Cherry") for bc.

weak oyster
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 $ date ; dc
Sun Jan  5 02:21:44 UTC 2020
5 3 * p
15
q
 $ date
Sun Jan  5 02:21:50 UTC 2020
spring pilot
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<flashbacks to Forth>

weak oyster
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 $ dc
8 k 22 7 / p
3.14285714
q
 $ dc
3 k 22 7 / p
3.142
q
 $ 
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So dc is very RPN-ish

spring pilot
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Yes.

floral iris
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So is the difference between bc and dc just that bc is infix? $ bc bc 1.06.95 Copyright 1991-1994, 1997, 1998, 2000, 2004, 2006 Free Software Foundation, Inc. This is free software with ABSOLUTELY NO WARRANTY. For details type `warranty'. 1 + 2 * 3 + 4 11 1 * 2 + 3 * 4 14

weak oyster
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I usually use galculator in Linux for RPN work, whereas on Android I have VKRPN by Valter Kiisk.

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@floral iris I think p is used in dc for print but that something else is used in bc (probably just a CR/LF).

spring pilot
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It is CR/LF.

floral iris
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That's what worked for me.

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And it was algebraic notation.

spring pilot
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It's been a long time since I had to do that.

floral iris
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I was a Hewlett-Packard calculator snob too. ๐Ÿ˜„ Now I just use Python.

weak oyster
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 $ bc
bc 1.06.95
i = 9 ; j = 7 ; i * j
63
quit
 $ 
floral iris
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(Just a cpio archive there...)

weak oyster
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dc is good on the command line when you're already there for some other reason.

spring pilot
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Huh? I'm always in the terminal. It's just what I grew up with.

weak oyster
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 $ echo "5 3 * p q" | dc
15
 $
spring pilot
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๐Ÿ™‚

weak oyster
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 $ echo '8 k 22 7 / p q' | dc
3.14285714
 $ echo '4 k 22 7 / p q' | dc
3.1428
 $
floral iris
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Python 2.7.6 (default, Nov 23 2017, 15:49:48) 
[GCC 4.8.4] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from math import *
>>> pi
3.141592653589793```
spring pilot
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Python 2 is depricated. ๐Ÿ˜‰

floral iris
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python3 means I have to type one more character

spring pilot
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And now my daughter is probably startled awake and wondering why I was laughing so hard.

floral iris
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This is kinda cute too, straight bash: $ printf '%x\n' $((77*466)) 8c2a

spring pilot
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As for pi... ```

pi

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(R)

floral iris
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What's doing that?

spring pilot
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The R statistical programming language. It comes pre-loaded with a raft of constants, including pi....

floral iris
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Ah... I used R pretty regularly when I was doing a lot of stats. I really liked it but it would be a big job getting back up to speed now.

spring pilot
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> pi
[1] 3.141593
> 
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I wrote an intrusion detection analytics platform in R back when I ran my own company....

floral iris
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And yet another Bell Labs connection... R is a free version of the proprietary S system.

spring pilot
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Only these days they back-port new R developments to S.

floral iris
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I don't doubt it.

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I remember getting weirded out by the S3 and S4 class systems though. It seemed like I should be using one or the other but I never could decide which one. ๐Ÿ˜•

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I get the impression though that it's very popular for analytics these days.

spring pilot
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A lot of people are moving to Python. Things like Microsoft's AzureML are R-based, though.

floral iris
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Ease of programming in Python... So many people know it and it's easy to learn if you don't...

spring pilot
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Yes, Python is great for prototyping. When it's time to do production work, though, you need something faster

weak oyster
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$ gforth -e '22e 7e f/ f. bye'
3.14285714285714
 $ 
 $ gforth -e 'pi f. bye'
3.14159265358979
 $ 
floral iris
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Well, I don't know how far we've advanced the frontiers of machine learning knowledge tonight ๐Ÿ˜„ but I'm gonna get up and try to get some stuff done. To be continued, I'm sure. Enjoyed the chatting.

spring pilot
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Yep, take care. (I'm actually working on unsupervised pattern discovery....)

river willow
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Quick general question; Does the values in my input layer need to be between 0-1? For some reason I made that assumption a while ago, but now when I've read more I don't see why that would be the case. Will be using ReLU if that matters.

Edit: Kinda answered my own question thru experimentation. Doesn't seem to be an issue with values outside that range, but I suspect normalized values is a big plus.

vestal coral
spring pilot
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If you'd like an overview of current state of AI, check out "Artificial Intelligence: A Guide for Thinking Humans," by Melanie Mitchell. (Full disclosure: Melanie is a friend and former research collaborator of mine.)

finite fox
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@arctic talon jojo

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ping me when yr here

finite fox
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@arctic talon hi hi

arctic talon
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@finite fox hi!

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perfect timing, just got here

finite fox
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gr8

arctic talon
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ready to look at the guide?

finite fox
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yes

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give me link

arctic talon
finite fox
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ok!

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first page needs a header gif

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put the best quality/largest you have

arctic talon
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should it be a repeat of the guide gif?

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i think that is the best one i have now

finite fox
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sure

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on this page

arctic talon
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or i have the one at the end of the last page

finite fox
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i dont care

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pick whichever you think is most demonstrative

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split the second page before Capturing Sample

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call the second page Visit Teachable Machine

arctic talon
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ok

finite fox
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the second half is confusing, it skips to the end

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guides should be in chronological order

arctic talon
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ok--well, idk if it skips to the end but it does skip pictures showing me dragging and dropping images to the page

finite fox
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rioght

arctic talon
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ok i can add those

finite fox
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they dont have them yet

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split the page

arctic talon
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oh i see wait, i accidentally hvae some stuff from the raspberry pi capture instructions still here

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my bad

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will rm that and add more imges

finite fox
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please do what im asking ๐Ÿ™‚

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can delete secondary page later if ya like

arctic talon
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did you look at the next page after this one?

finite fox
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yep

arctic talon
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ok

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doing

finite fox
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close but...

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i meant to split at the scerenshot i pasted

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i will fix

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dont do anything

arctic talon
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ok

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hm, you want them to capture samples first then visit TM?

finite fox
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split here

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on this page

arctic talon
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K, wait and to do that do you copy the page or?

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oh the button

finite fox
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split page

arctic talon
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Ok, so did that but should i swap titles?

finite fox
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you split in the wrong spot

arctic talon
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?

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ugh

finite fox
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ok stop

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i will do this

arctic talon
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sorry

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ok

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i think i'm confused because they should really set up the teachable machine project as the first thing they do

arctic talon
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ok cool

finite fox
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do you need these pictures

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do you have them backed up somewhere

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if not back them up now

arctic talon
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no

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they can go

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they are on the Raspberry Pi page and should have gotten deleted

finite fox
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ok add text at the top of this page

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so it doesnt skip to an image "transistor" without intro

arctic talon
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ok, will take over page

finite fox
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you'll also need to re-shoot the bottom pic

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cause it has images in it, and it shouldnt (?)

arctic talon
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yeah so i think that's the pic i am missing

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can easily reshoot

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do you want me to move the "Choosing Samples" text from "Visit TM" page to "Create Categories" page?

finite fox
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i dont think so...yet

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its ok where it is for now

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lets get the create categories page in good shape ๐Ÿ™‚

arctic talon
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k

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wrote some things!

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can make more bulleted if you prefer

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also need to write instructions on how to input the categories into TM

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doing that now

finite fox
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yep

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so this page...

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has some pix

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but it gets confusing becuase it doesnt match the previous section

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so remove and just have one 'creating categories' for electornics page

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then we will either use cam OR upload

arctic talon
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ok

finite fox
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for ginourmous images like these

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where text is large, make into a 'side2'

arctic talon
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ok

finite fox
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and add text above/below so its side/side

arctic talon
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i'm moving that to Create Categories pge

finite fox
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dont use for high-res images cause of course the resolution is smaller ๐Ÿ™‚

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yah

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im on that page

arctic talon
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right i see now

finite fox
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im in aonther window so @ me for atten

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i gotta zzz at 11

arctic talon
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k

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@finite fox ptal

finite fox
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oki

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ptal?

arctic talon
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i could take over Create Categories now too

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oh sorry, please take a look

finite fox
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oh yah

arctic talon
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from old job

finite fox
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ok lol

arctic talon
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lol

finite fox
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lgtm i know ๐Ÿ™‚

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ok im lookin at webcam page

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gopher it

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(g4i)

arctic talon
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lol k

finite fox
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gr8 use of side2

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showing after you add the iamges

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the 'roll' of images

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you can do just one category

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and let em know they should repeat for alll categories

arctic talon
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k

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done with Create Categories

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@finite fox done

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will capture an image of me uploading for Raspberry Pi Camera page

finite fox
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ok

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k00l

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reviewing

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good - i think this camera roll image is going to confuse people tho cause its in a corner of a whitebox? plz shoot the pix of the cap so its larger and with flat background...

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otherwise its a corner detector ๐Ÿ™‚

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ok moving ahead

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remove samba instructions - always point to extenral resource, ideally official raspberry pi

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because samba setup changes

arctic talon
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ah okay

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i can reshoot.

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i know what you mean

finite fox
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add a screenshot for this:

arctic talon
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the problem is the external instructions are already out of date

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the command to restart server doesn't work

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๐Ÿ˜ฆ

finite fox
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yeah LINUX

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is this guide better?

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i really odnt want to have the instructions live on this guide

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it will bite us

arctic talon
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looking

finite fox
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ok i am going to pass out, please add images to remaining pages

arctic talon
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yep seems so

finite fox
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its got good bones ๐Ÿ™‚

arctic talon
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cool thanks!

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will send email when i'm done

finite fox
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i made a few pages 'published' which means i reviewed

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dont publish other pages, cause thats how i keep track

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ill do the rest l8r

arctic talon
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ok sure

finite fox
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after my eyes work again

arctic talon
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thanks for staying up so late

finite fox
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zoom bye! ๐Ÿ™‚

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np

arctic talon
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bye!

hoary fern
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Hey

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can anyone help me over here?

rancid fossil
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I don't know, can you be more specific? If you want help with IBM PowerAI, I probably can.

rich schooner
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thx in advance for any help given

timid python
dusty thorn
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Hello all I am not sure if computer science help is out of reach of this community but I have been looking at loading in the Kaggle Grasp and Lift data set into some AI that is not related to the kaggle competition and I was wondering if anyone could give me some guidance or advice on how to do this I have previously used torch and numpy to load an ISIC dataset of dermascopic images of skin lesions into an AI but I don't believe the same will work since the Kaggle dataset is EEG recordings not images. Any guidance?

weak oyster
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cool

weak oyster
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Hello, I want to learn machine learning soon. Do you know good website or book to learn?

rancid fossil
dim valve
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i got a remote machine learning research internship as a HS student im a bit familiar with tensorflow, sklearn, opencv, and numpy but im not doing vision related stuff for this intern and i donโ€™t have too much experience with ml

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are there any recommendations for ml books (python or r preferably)??

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im self taught in multivar calc, linear algebra and statistics (self-studied for ap stats, got a 5)

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i also have tensor and vector analysis books too from a friend who's a math major

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so i think im fine with math

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but not sure with ml so that's why i thought it would be nice to have a ml book/pdf

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ive made cnns for facial recognition and cancer detection but those are the only two ml-projects ive made so far and know basic stuff like random forest, svms, regressions, knns etc.

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so im not really confident rip

rancid fossil
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Pull quote: "In practice: use whatever works best on ImageNet. If youโ€™re feeling a bit of a fatigue in thinking about the architectural decisions, youโ€™ll be pleased to know that in 90% or more of applications you should not have to worry about these. I like to summarize this point as โ€œdonโ€™t be a heroโ€: Instead of rolling your own architecture for a problem, you should look at whatever architecture currently works best on ImageNet, download a pretrained model and finetune it on your data."

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I'll also point out that Keras is your friend.

dim valve
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ah yes forgot to mention keras, but thank you for the link @rancid fossil

rich schooner
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hey everyone...I'm working on a machine learning project where I'm using a neural network to solve a binary classification problem, however, my dataset(in .csv format) is relatively small. It only has around 60 yes/no cases and although it was able to train, the accuracy wasn't very good. My solution to that was just duplicating the dataset and on each duplication, making tiny changes to the numbers, i.e., adding +-1 or multiplying by 0.999 to each number. By doing this I grew the size of the dataset to around 1100 new cases and it achieved much higher levels of accuracy. I was wondering if this is an actual technique used by ML researchers and if it is, does it have an actual official/academic name?

fast hill
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It is a known technique, but I'm not sure it has an official name. https://machinelearningmastery.com/train-neural-networks-with-noise-to-reduce-overfitting/

Training a neural network with a small dataset can cause the network to memorize all training examples, in turn leading to overfitting and poor performance on a holdout dataset. Small datasets may also represent a harder mapping problem for neural networks to learn, given the ...

rancid fossil
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I think the general term is "data augmentation"

rich schooner
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Alright thanks. I have to write a paper on it and so I didnt want to come across as unprofessional or smthg lol by not using the proper term

white fulcrum
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So I'm still not sure what happens in this channel, is this channel that observers the growth of machine learning, or is it kind of like a collaboration to try to make a machine learning algorithm?

fast hill
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It's just for discussions and questions on the topic of machine learning.

white fulcrum
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Oh, I see

daring lichen
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I mentioned it briefly in the IoT channel, mixed in with another comment, but has anyone seen the SparkFun Artemis Module? I have been using it for ML and it is a great idea as it makes implementing a MCU in a project much easier and less of a hassle since you don't have to piggyback boards. The only problem is the MCU itself is an Apollo3, which is not quite ready for use in the maker community, and requires a lot of small adjustments to make most libraries work with it. This made me think of having a similar board, but one which runs off an M4 instead. This would be more supported and still offer the machine learning potential (which is why I brought it up in this channel) and could be programmed without a USB to serial converter, which would make it even easier to use, just to name a few advantages of the M4. Anyone have thoughts about this? It seems like something that would fit in well to the M4 board collection.

rancid fossil
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I have one of the Artemis modules, but I'll admit I haven't hooked it up or done anything with it yet.

daring lichen
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Right now, the only similar option I can find to the 'micro controller and supporting circuitry on a surface mount board' is a ESP style module, but they don't seem quite as elegant/friendly. Do you know of anything similar? I would also be more than happy to work on such a thing if anyone else would be interested.

ornate flower
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@rich schooner you might want to look into approaches that work well with small samples instead of data augmentation for example k-shot learning. Data augmentation can lead to serious overfitting.

rich schooner
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@ornate flower i looked into k-shot learning and its definitely a really interesting approach. Could you recommend any tutorials which teach u how to implement it(preferably in python) since all the resources i could find were heavy in the theory and math?

ornate flower
muted ocean
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Has the pyBadge replaced the pyEdgeBage for machine learning?

muted ocean
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I was wondering what the preferred development board would be. The Clue Board looks amazing.

stone dirge
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The EdgeBadge has a built-in microphone which you can add externally to the Pybadge, but functionally I think they are equivalent.

daring lichen
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@muted ocean I think the preferred development board depends on what you are trying to accomplish. Clue and EdgeBadge have a lot of built in functionality, but there are also other boards better suited for breadboard type prototyping, if that is what you are looking for. Are you hoping to train your own models or use prebuilt models?

muted ocean
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I'm looking to use either prebuilt or custom trained. I'm looking to use them for projects to take a sense/sensor like sound, light, motion and filter them with ML back to a robot or desktop system/Raspberry PI. I'm looking to eventual build a workshop around the concepts.

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I'm also looking USB HID support in the device. I'd like to take custom inputs and map them to common HID devices.

daring lichen
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Very interesting, hope you the best with it. Sounds like any M4 based board would work well.

oblique mirage
keen tide
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I recently got into machine learning ( like in December) and was wondering if anyone had any recommendations for free machine learning courses I could take to further my knowledge

ornate flower
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@keen tide depends on what you are most interested in. Fastai has great content on DNN (https://course.fast.ai/), for RL David Silver has a great series of lectures online https://www.youtube.com/watch?v=2pWv7GOvuf0 (Ideally you should be confident in DNN already), along with deepminds Spinning up RL (https://spinningup.openai.com/en/latest/). For more classic approaches check out the courses on kaggle https://www.kaggle.com/learn/overview Also worth using kahn academy to solidify your maths skills if necessary.

#Reinforcement Learning Course by David Silver# Lecture 1: Introduction to Reinforcement Learning

#Slides and more info about the course: http://goo.gl/vUiyjq

โ–ถ Play video
keen tide
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Alright thank you

rich schooner
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when the graph looks like this, what does it mean?

rancid fossil
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It trained really fast, and the 100% test accuracy implies that you may not have enough test data. Since the accuracy went down, it may have overfitted.

rich schooner
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so do u think that maybe with a bunch more training data it would perform better?

rancid fossil
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That would be my guess, but all I have to go on is the accuracy graph. Do you have a loss graph?

rich schooner
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i dont have a loss graph(ill make one) but i increased the training and validation data and this is the new accuracy

rancid fossil
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That looks pretty solid, but it looks like it's basically done by epoch 20 or so. It's faintly odd that it's usually more accurate on the test data.

rich schooner
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ok i did a bunch of stuff to it, including adding dropouts and experimenting with batch size, and this is the final graph

lunar raptor
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yo, im trying to understand the calculus behind propagation in neural networking

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here, im confused as to how chain rule is applied here

rancid fossil
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That looks like it's just a simplification (the โˆ‚z and โˆ‚a terms appear to cancel out)

lunar raptor
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ah ok

clever blade
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That's the whole point of the chain rule. ๐Ÿ™‚

onyx pasture
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has anyone worked with edge ai

fast hill
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Haven't worked with it myself, but there's a TinyML community out there which is pretty interesting for low-power edge AI.

onyx pasture
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i've looked at it a bit

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I'm just trying to understand more scenarios for using it

clever blade
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In general ML can be used instead of heuristics. If you're reading something from a sensor and are using heuristics or rules to make sense of the data, you might be able to get better results if you're using an ML algorithm.

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A typical use case that comes up in a lot of TinyML demos is anomaly detection of vibrations. Take an MCU with an accelerometer to do vibration readings. If the readings are out of the ordinary, send some kind of notification.

white fulcrum
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Just curious, but does anyone know any simple ML programs that can be easily tested, and is easily accessable?

rancid fossil
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I'm not quite sure what you're asking, but you can quickly get started with simple exercises with Keras (local) or Colab (online).

clever blade
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There is the TinyML book by Pete Warden and the other guy, that has a lot of examples.

daring lichen
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@white fulcrum I'm not sure if you mean just ML or TinyML, but I recently started learning Tensorflow and created an easy to follow, stripped down introduction to TinyML. I used an Artemis board, but the Adafruit M4 based boards work with it as well. It's as simple and accessible as I could make it, offering even a way to use it just through the serial monitor, or with a few buttons and LEDs. It is up to date unlike most other TinyML guides I tried using before. It can be found on my Github: https://github.com/TSprech/Easy-Tensorflow-Lite

white fulcrum
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That was my bad for not being clear, I'm just uncertain about where I should begin with ML

daring lichen
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At least that was my starting place, there are many out there.

kindred flume
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@white fulcrum Honestly, do not start with Deep learning or even tensorflow for that matter.

onyx pasture
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keras is relatively easy to use but i would recommend actually learning what it does first

kindred flume
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If all of my machine learning classes that I teach I start with very basic machine learning techniques like logistic regression then we move through the others such as decision tree, random forest, SVM, and end it with perceptrons. Then there is a whole other class on deep learning.

onyx pasture
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i did a course on sololearn for ML i think

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it went through more basic ideas and ended with neural networks

kindred flume
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To understand NN/DL I would suggest you look into perceptrons.

white fulcrum
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Got it, I'll start learning about ML with what you all recommend.

kindred flume
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You can learn a lot of this stuff from just videos on youtube as well

clever blade
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You can start with deep learning just fine and then work your way back to classical ML algorithms, but most courses expect you to do it the other way around. So if you start with deep learning, the course may assume you already know basic ML.

white fulcrum
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Got it, so far, ML seems like a lot of fun, and something that takes more than a month of study

keen bluff
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Hi Iโ€™ve never done any machine learning or anything like that, but I know I little bit of python. Do you really need to know a lot of stuff before doing tinyml?

fast hill
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There are plenty of different levels of difficulty, depending on what you're doing. You don't need to know much to follow a tutorial, but tackling some more advanced stuff is still active PhD-level research.

onyx pasture
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a lot of the documentation is very specific

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as in if you don't have like a nano ble sense ur screwed

daring lichen
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@keen bluff I don't want to double up on this topic in the chat, but I actually tried making a decent (still not perfect) extremely simple introduction to taking machine learning from Google Colab to train all the way to computer independent Arduino TinyML because I faced the exact problem @onyx pasture mentioned of needing a Nano BLE Sense for anything, and decided to fix that. My example works on pretty much any ML capable (often one with an M4 controller, such as Grand Central, Bluefruit, etc), and is meant to be beginner friendly as too many guides are either too advanced or outdated. The link to that Github for it and a little more info can be found about 12 comment back in this chat as a response to Rotom. This will also let you judge how comfortable you are with the ML/python skill required. Hope this helps!

onyx pasture
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thats pretty nice

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i also found another library called eloquent tinyml and it worked for me

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for a nodemcu

daring lichen
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Thank you, and yes, that library really helps streamline things. What I discovered to be the hardest part is creating your own properly trained model, as I found the TFLite converter is extremely temperamental for TinyML

onyx pasture
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yeah tbh I haven't really tried to do my own classification problems since I don't have any sensors or anything

daring lichen
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What kind of problems do you mostly work with?

onyx pasture
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I'm still a beginner so I haven't done a lot

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I think the only successful project I did was the starting sine model prediction on a nodemcu

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I also tried using one of sklearn's datasets, but it had multiple input features

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and that gave me a bunch of errors when working in arduino

daring lichen
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It seems like you've seen similar problems I have. It's been difficult recently to get decent, up to date, guides with how quickly machine learning evolves, and getting support is hard because there are hundreds of new issues on Tensorflow's Github every week.

onyx pasture
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Yeah

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And documentation for a lot of things is lacking

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I also tried purchasing a new development board but theres not very many helpful resources

clever blade
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It's also still very early days for TinyML. There's no "killer app" for it yet.

daring lichen
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Yeah, trying to find a board was tough because at first it seems like you have only a handful of options, but so many dev boards work with it. The problem is that it's so new like matthijs said, no one really has tried venturing outside the box.

clever blade
#

Of course you also don't need to use TensorFlow. You can implement the logic yourself and simply use the weights from the trained TF model. It can be a bit of work to implement this but it might be less work than getting TensorFlow to run on the board. ๐Ÿ˜‰

rancid fossil
#

TensorFlow Lite can be a useful approach for that.

slim wing
#

hey guys, is there a good book about machine learning for beginners? (hopefully an ebook)

clever blade
#

@slim wing I always recommend Introduction to Machine Learning with Python from O'Reilly.

slim wing
#

Thanks a lot!! ๐Ÿ˜ƒ

cunning atlas
#

Hello.

#

Does anyone know where I might find the link to the code for @lilac chasmโ€™s project from show and tell?

#

For the OV7670 streaming to the TFT using a SAMD51.

onyx pasture
#

you might want to take a screenshot of that project or something

cunning atlas
#

I would like to try to implement/modify it.

#

How?

onyx pasture
#

like screenshot their post

#

i don't see it in show and tell

cunning atlas
#

I donโ€™t think they made a post for it.

onyx pasture
#

maybe you could try asking in another channel

lilac chasm
#

For the OV7670 streaming to the TFT using a SAMD51.
@cunning atlas Itโ€™s in a private repo for the time being. Will make it public once the codeโ€™s not a tangled mess.

weak oyster
#

How would i train a yolo3 model for eye tracking?

clever blade
#

@weak oyster There are plenty of YOLO implementations on GitHub, for all training frameworks. The most important thing is that you need a dataset where all the eyes have been labelled. However, using object detection to do tracking isn't the most efficient method. Often people use object detection to find the eyes and then use a separate tracking method for following them in the next frames, until you lose them and then do object detection again.

weak oyster
#

Exactly what i was thinking

harsh maple
#

Would a convolutional network work well in this instance for pattern regonition of the eyes @clever blade? I understand the low levels of MI but havnt done much implementation (Just curious)

clever blade
#

@harsh maple Yes, something like YOLO is a convolutional network.

#

(Of course, you can also use simpler methods such as Haar cascades. You don't need a neural network for this, but they are usually the most accurate solution.)

harsh maple
#

Well I wasnt talking about a nerual convolutional network, just a simple convolutional network but glad to know in the end what should be used

clever blade
#

What is the difference between a neural convolutional network and a simple convolutional network, @harsh maple ?

harsh maple
#

A nerual convolutional network uses a neural network to generate the convolutional filter while the "convolutional network" (I think technically in this case it is just called a convolutional filter) uses a matrix hard coded and defined by the implementor is my understanding.

clever blade
#

Ah I see what you mean. Yeah there are methods like that, such as Viola-Jones.

harsh maple
#

I guess when its running in production there is no difference since using a nural network is just for training to get a end multiplation matrix. Very interesting, reading about it now, I really need to dive into ML, I've just been focusing on using DSP SIMD in M4 processors for acceleration and not the actual implementations/application of MI to things like say, finding eyes

clever blade
#

Well, there are some differences. With something like Viola-Jones you run a small pattern matcher over the image (i.e. like a convolution with a fixed matrix) but then you train something like an SVM to predict stuff using these patterns. With a neural network, the prediction is not done using a separate model (such as SVM) but in the neural net itself.

rancid fossil
#

I'm just lurking, but this is really good info, thanks!

night lynx
#

what if i want to do "object" tracking in 1 dimension?

#

do any of these algorithms work on an image with height = 1 pixel?

onyx pasture
#

why would u want 1 dimension

#

there are definitely algorithms for 2d images

night lynx
#

signal processing

onyx pasture
#

im not really sure if that would work

#

you could try it out with a pretrained model

night lynx
#

i'm not sure how though because they need a 2d image. i could just duplicate the samples vertically to get something that looks a bit like a bar code

onyx pasture
#

Well it's still 2d if it's one pixel tall

#

You could maybe try duplicating it

night lynx
#

green = detected data, red = empty

#

see how all the green lines begin with the same pattern?

#

i need to do three things: 1. detect the lines that have that pattern, 2. detect where in the line that pattern is to a high degree of accuracy, 3. decode the rest of the data in the line

#

but this is complicated because the pattern looks different depending on signal quality and also moves around (it is not always lined up like in the picture)

#

my current algorithm assumes that the pattern will always fall between the two vertical green lines but this is not always the case

#

the noise and signal level can both be different and also there can be blurring and ghosting in the signal

fast hill
#

Some of the 2D image-recognition architectures probably wouldn't be very suitable because their connectivity is explicitly geometric, so they can pick up local 2D structures like edges. But since a 1D data set has so much less information, you can get away with a lot fewer neurons and throw a fully-connected net at the problem if you want.

night lynx
#

hmm okay, i'll keep that in mind, thanks

shrewd ginkgo
#

Hi all, I've been distracting myself by thinking about long term ideas today and I'm wondering if I could expand an existing idea about a touch screen that would manually record which cats are inside or outside. The original idea was just to have a touch sensitive display where I would adjust it each time I let a cat in or out. But in overthinking it further just now, I was wondering if this could reasonably be done with ML and a camera pointing down at the bottom corner of the slider and recognizing: door closed, door open but empty, Annie going in, Annie going out, Beth going in, Beth going out. I guess I need to collect images from the camera over a couple of days, run the training step on some bigger machine, and then download the results to the edge device where the camera is. Does that seem like a reasonable approach? It'll be a while before I get the time to work on, but I could do some reading in preparation if people think it might work.

night lynx
#

somebody already did this

#

i think they only had one cat though

#

a guy managed to train ML to recognize when his cat was trying to bring dead animals into the house, so i think it is definitely feasible

onyx pasture
#

if you aren't super confident in your ability to create your own cnn i would suggest trying to maybe find some software that allows you to create a custom network

shrewd ginkgo
#

Well, from what I'm hearing TensorFlow isn't so hard to get to do this. I've been programming for over 50 years, and with about 60 languages under my belt I no longer find anything with computers that I can't grok easily.

onyx pasture
#

if you're thinking of running the network locally on the device, you might find some constraints, but otherwise I don't think there should be too many issues

clever blade
#

Another option is to use an RFID reader if the cats are chipped.

shrewd ginkgo
#

I've thought about that@clever blade but I think the reader would have to be pretty close and the cats seem to prefer going through as close to the open door as they can (i.e. as far away from where I could mount a sensor), and I think detecting the difference between coming in and going out might entail too much.

rancid fossil
#

A separate pair of beam break sensors could help determine direction of travel

weak oyster
#

any danger in having a IR led near my eye?

clever blade
#

I wouldn't put the pointy bits in your eye.

stone dirge
harsh maple
#

Afternoon all, Im trying to work on my first ML project that takes data from a 8x8 IR sensor and just outputs a binary true or false if there is fire present. I was wondering if anyone had a good recomendation on what sort of algorithm I should start with, I would think it needs a form of short term memory but I'm not certain on what other constraints I should be looking for in the infinite examples online.

#

I could probably do this with just some basic logic, but I want a ML project gosh darn it!

onyx pasture
#

are you just running the machine learning algorithm on your computer

harsh maple
#

Idea being to do any sort of training and tinkering on the computer, Im streaming my data over TCP for the moment from a ESP32, but with the end implementation running on a M4 ARM processor once I get everything figured out. I have been learning in depth the M4 SIMD instruction set so I plan to use that to accelerate predictions.

onyx pasture
#

you might only be able to do image processing and not video processing

#

the hard part for me was just finding the right software to do it

#

make sure your dev board is supported by whatever program you are using

harsh maple
#

I feel like image is a strong word here, there are only 64 "pixels", and I get them from a 0-1 float value so I thought they would make quite good inputs for basic ML algorithms. 64 input to 1 output. But I dont really need "video", just short term memory to infer between two frames which can be upwords of 30 seconds apart

onyx pasture
#

I feel like making your own CNN is pretty possible

#

but the problem comes with running it on the cortex m4

#

i had to use this website called edge impulse to make optimized code

#

but i dont know if the website supports very many inputs

harsh maple
#

Well for a convolutional network the M4 has a SIMD instruction for matrix multiplation, I would think for small images it would make for a good CNN processor, but I also would have thought a CNN would both be over powered, and I thought they lacked memory.

onyx pasture
#

i think people have gotten CNN's to work on m4's

#

im not sure though

harsh maple
#

Certainly. Im just not sure its the right tool for the job

onyx pasture
#

yeah

#

i guess you can try using a basic neural network?

#

if you are concerned about memory

#

maybe try other learning algorithms such as svms

#

this blog has posts about running machine learning on smaller microcontrollers

harsh maple
#

That might be a good thought. Ill also look into SVMS. Im not as worried about the implementation, just finding what ML algorithm would be the right tool for this job.

#

That article mentions SEFR which looks promising, it produces a binary output

onyx pasture
#

yep

#

since its binary classification there will probably be lots of optimized algorithms out there

harsh maple
#

Sure, thanks, I will read up on SVMS, SEFR, and if those dont fit just look into different neural network topologies which might fit.

fast hill
#

Though for fire detection a neural network might not be needed. "Any pixel has a temperature above 500 degrees? Probably a fire!"

#

The net would just be learning a simple threshold rule in training, most likely.

harsh maple
#

True that, its just the sensor is far away, and its not black and white as saying if this pixel is over 500 because the sky and reflections from the sun will set pixels to be max value. However I am conditioning the data to slowly average out in order to prevent the environment from giving me false positives.

fast hill
#

Gotcha

harsh maple
#

It may be as simple as just looking for abrupt changes in temp I guess.. Will be setting crap on fire later today to see what my data looks like ๐Ÿ”ฅ

wet jewel
#

sorry, but thats kinda funny!!!!(setting crap on fire today)......am reminded of The IT Crowd, where he has the fire extinguisher, and it's on fire, and he says "I'll just set that over here with the rest of the fire..."

onyx pasture
#

I'm trying to work on a new tinyml project on audio classification

#

does anyone have any ideas or examples of what I could do

clever blade
#

My toy idea for this was wakeword detection for a robot that tells silly jokes. You'd say "tell me a joke", which activates the robot. It picks a random joke from its database and sends it through text-to-speech. @onyx pasture

onyx pasture
#

Thanks for the idea

#

I may also do wake word detection but I don't want my family to think I'm insane when I'm saying the same word over and over

kindred flume
#

@onyx pasture arduino also supports KNNs

onyx pasture
#

oh yeah

#

forgot about that

#

@harsh maple you may want to know that

kindred flume
#

It's really awesome but the most critical is optimizing the n

#

Oh also, arduino has 1 class SVMs

#

Useful for anomaly detection

#

Could be useful for fire detection as it's an anomaly

#

@harsh maple

harsh maple
#

Awesome, thanks I will look into it @kindred flume

real sparrow
#

can OpenCV run on a RasPI3B+ or is a big struggle ??

#

which OS is best for this , Raspian??

stone dirge
real sparrow
#

ohhh coool -- PS im tryinghard not to reinvent the wheel , this is why i ask

stone dirge
#

the may be out of date -- it was for stretch --

real sparrow
#

i know i had to use python 3.7.5 , 32bit on a PC because of library conflicts in OpenCV

#

hmmm im guessing Raspian is being updated so , OCV can be pip easy or may already be installed???

#

mmmm i take clues from as many sources as possible -- because , one may have a nugget of code or whatever

stone dirge
#

certainly worth trying the pip3 install

real sparrow
#

yesss i will do - thanks

kindred flume
#

It runs pretty good tbh

#

I'm using it for some research and it runs great. Pip install it

#

Also going to try openvino but that's a different story

finite yoke
#

I am planning on creating a CNN model that can identify an abnormality within an image. However, I want only a certain 'piece' within that image to be identified (ie. the eyeโ€™s in an image of a face). How do I make that work? Do I have to use another algorithm, if so, what is it called?

clever blade
#

That is called object detection.

finite yoke
#

Oh ok, thank you so much!

kindred flume
#

@finite yoke use an autoencoder and segment the image

#

Object detection wouldn't necessarily find anomalies

clever blade
#

It depends on their use case. I assumed the intention was to first identify the eyes, then do anomaly detection. But if detecting the eye itself is part of the anomaly, then object detection won't work indeed.

kindred flume
#

In the case of detect the eyes then anomalies it would be CNN->autoencoder

willow quarry
#

can i implement machine vision into arduino?

#

CNN

fast hill
#

Unless you mean a very low-res sensor, you'll probably be happier with a Raspberry Pi sort of board instead of an Arduino. The software infrastructure with OpenCV and Tensorflow is also friendlier there.

#

Something like this would also be an intermediate solution: https://openmv.io/

onyx pasture
#

^ that also works with edge impulse, which is a pretty helpful online software for building networks

clever blade
#

Check out the TinyML book by Pete Warden & co for examples on how to use CNNs on microcontrollers.

willow quarry
#

Ive been swapping between microcontrollers trying to find a good one and i guess was trying to get ai on the mega to work

#

i also tried using the pca9685 to control servos with the rpi but I couldnt really work it out even with adafruits tutorial

#

I can get one thing to work on one microcontroller but cant get another to wokr

kindred flume
#

I wouldn't recommend it tbh. I'd recommend you use a raspberry pi for the CNN.

#

Not sure what you're using it for but you'll get better processing time on the pi

raven bronze
#

nvidia embedded is now supporting ONNX Runtime

harsh maple
#

Thats interesting, I was just looking into ONNX recently, looking at their deploy hardware section Qualcomm and Rockchip are listed amung some IP vendors so this has some interesting implications.

#

I was wondering the other day if it was possible to create a compiler with this standard as input to output a C implementation with the ability to hook in platform specific libraries for SIMD for cheap edge devices. With the thought you could use tools such as colab to create basic models

raven bronze
tawdry narwhal
finite yoke
#

So I have been using VS Code for a while now and everything was working well. I am coding in python and learning regression, however the run button just vanished. Like I am unable to run my code and I closed and reopened the application but nothing seems to work. Any idea why this is happening? (BTW, I'm on Mac)

light plume
#

Do you want to learn about the latest technology in deep learning used by the experts in teaching and industry such as fastai, PyTorch and Jupyter? I highly recommend this free course from Jeremy Howard and the University of San Francisco https://www.youtube.com/watch?v=_QUEXsHfsA0

Welcome to Deep Learning for Coders! Be sure to watch these videos through https://course.fast.ai to get access to the searchable transcript, interactive notebooks, setup guides, questionnaires, and so forth. We don't recommend watching the videos directly on YouTube.

In this...

โ–ถ Play video
light plume
#

@ripe night would CircuitPython be able to implement fastai and PyTorch? Would love to hear your thoughts on this!

ripe night
#

@light plume not likely. The closest thing I can think of is tensorflow lite. It runs from arduino now but we could likely build an api to it from circuitpython

light plume
ripe night
#

I haven't heard of one but an embedded version would be the place to start.

light plume
#

I'm a fan of nRF5 SoC's and I use them for my work quite often

#

Adafruit use them on a number of boards too

#

I believe on some of their feathers?

#

@ripe night how's your coverage of FPGA going lately? Is it hard to go into areas like that when you know your fanbase is 90% interested in ESP32 S2? I think you're doing great work btw and I hope you steer people into areas they never thought about before.

ripe night
#

we have an nrf53840 feather

#

fpga is my side interest

#

-s2 should be cool too

light plume
#

I hope you're keeping track of the ULX3S board. Jump on https://gitter.im/ulx3s/Lobby and prepare to be amazed by the amount of work going into supporting this board. I am also a big fan of iCEBreaker but I think ULX3S is going to be big

ripe night
#

I'm focussed on the low end atm

#

hoping to bring basic fpga stuff to the $20-30 range

clever blade
#

The people moving from TensorFlow to PyTorch are mostly researchers. At this point, it's still a lot more tricky to put PyTorch into production than TF. Also note that TF Lite and TF Lite Micro are totally separate runtimes from the main TF. In theory someone could make a PyTorch-to-TFLite converter and you'd be able to run your PyTorch models on TFLite-enabled boards (but keep in mind that TFLite and TFLite Micro are way less powerful than the full versions of TF and PyTorch).

rancid fossil
#

Some engines (like IBM's Power AI Vision platform) generate models in a variety of formats (some of them PyTorch). This bit me when I wanted to export a model and run it on another platform!

finite yoke
#

Hi! I had a quick question. I am currently making a CNN model, and there was no pre-made dataset available for my use case, so, I made my own. I collected images online, and split them up in train, test, and validation. I was able to collect all the images, but, I cannot find a way to load this custom dataset in to my code. All the tutorials I have come across, are all for datasets that are pre-made online.

So, I was wondering, if you guys know any tutorials or know how to load the data in that was custom made by myself. Thanks in advance!

fast hill
#

That would probably be dependent on the framework and environment in which you've created your model.

rapid dock
#

this may be a stupid question, but what's a language similar to python syntax that works well for machine learning/creating a neural net, or is python already a suitable choice? All I have knowledge in is python. Please @ me, I won't notice a response otherwise. ๐Ÿ™‚

fast hill
#

@rapid dock Python is indeed commonly used, with frameworks like TensorFlow or PyTorch.

upbeat stratus
#

lisp have been dropped fror machine learning?

#

i'd think it'd be great since it can literally build and return functions

fast hill
#

Modern ML tends to be more about churning through big matrices than representing logic in the code and recursive data structures.

upbeat stratus
#

interesting

rancid fossil
#

Lisp is still used, but it's not as currently popular as CNNs and the like. There are a few businesses using Lisp that are quietly doing quite well, as they can field new functionality very fast.

clever blade
#

I don't think Lisp has really been used for "machine learning" so much, but rather for symbolic AI.

raven bronze
#

CNN and others is now also by microsoft getting bigger to .NET languages too

#

as SciSharp Stack is open sourced what brings python to .net as what comes to Machine learning, Data Science and AI

gloomy lake
#

Madbodger who are some of those companies, I'm curious. LISP certainly has its ardent fans. From what I've observed even in fields like NLP they are moving from a symbolic approach to 'throw deep learning at it'. Oversimplifying of course but it does seem symbolic AI is pretty dead

rancid fossil
#

One of the companies using Lisp internally is Sabre, who builds an airline reservations backend.

gloomy lake
#

oh that's very interesting. They're huge

ornate flower
#

googles teachable machines could also be a quick and easy way to explore your usecase if you are less interested in the actual ml.

rapid dock
#

I'm trying to get this python camshift algorithm to work, but every time i run it the output window won't respond.

#

Please @ me, I won't notice a response otherwise.

rapid dock
#

I don't get an error in the shell, and camera does turn on...

rancid fossil
#

@rapid dock Sometimes waitKey() doesn't work very well

marble bison
#

hey all, starting to learn and play with TensorFlow/styleGAN mostly for fun/creative reasons. Wondering if there are any StyleGAN specific discords anyone is familiar with?

#

ive tried searching, and I think this is the best I've come up with so far! (adafruit/machine-learning)

marble bison
#

kinda surprised that there's no UI projects for stylegan (or if there are, just hard to find) so I started on one. It's a bit ugly and clunky now but it can launch into an anaconda virtualized workspace and issue python commands (nodejs + python)

true bronze
#

what would be the easiest AI/machine learning i should search for and learn so i can understand the basic algorithms and all that other good stuff

clever blade
true bronze
#

oops

#

sorry for not being detailed

#

i meant with python

wicked parrot
#

Not sure if there is a tinyML library for CP yet

true bronze
#

i mean regular python

#

no microcontroller

#

no nothing

wicked parrot
#

Oh gotcha

true bronze
#

just python

clever blade
#

If you're asking in general (not related to embedded) then there are literally hundreds of beginner courses / videos / blogs on AI & ML these days.

#

Personally, I'd recommend the fast.ai course.

true bronze
#

wdym by embedded

#

?

true bronze
#

ok

clever blade
#

And the book Introduction to Machine Learning with Python from O'Reilly.

true bronze
#

ok

#

i will take a look at the book

#

don't feel like paying right now

#

cause idk if i will like it or not

clever blade
#

Like I said, lots of other courses etc online. Many for free.

true bronze
#

ok

#

will also look at articles

keen tide
#

I've a question about NEAT algorithms

#

Im working on my own implementation, but Im having issues with my connection mutations

#

Occasionally my program will create a connection with the same in node as out node

#

is this allowed, because I feel like it shouldn't be

#

if anyone has an answer or can help me could you please ping me as I only have ping notifs on

astral glen
#

requesting some help with installation of Tensorflow
should I just stick to guide on official website or a few suggestions from yt vids show installation of stuff like anaconda, cmake so any guides that are latest ?

rancid fossil
#

It depends somewhat on what you're doing. Anaconda installs a whole bunch of stuff at once, which is handy if you want to use many different libraries and don't want to install them individually. However, if you're just using Tensorflow, it's easy enough to install on its own. Note that some things depend on Tensorflow 1 and some on Tensorflow 2, and for some platforms, there's a GPU-enabled version.

#

If you're doing heavy processing, it can be useful to build Tensorflow for your particular setup. This is a fairly long process, but will take advantage of whatever features your CPU (and GPU, if supported) offer for best speed.

#

Note that I rarely use Tensorflow directly, these days I'm either using Keras (if I'm doing machine learning directly) or software like Rasa that uses Tensorflow internally.

clever blade
#

I'd add to this that TensorFlow is always changing, so whatever some YouTube video shows may be out of date information already.

rancid fossil
#

Good point. This is why I normally let packages that use TensorFlow install it themselves as a dependency. That increases the likelihood that the combination will work together.

clever blade
#

I personally use Anaconda to manage the packages, but that's because I often need to switch between different environments. Especially on the Mac it can be a hassle to keep your Python installs clean otherwise.

rancid fossil
#

I switch environments pretty often as well, but I'm using virtual environments to do so.

clever blade
#

The problem on the Mac is that the system Python is 2.7. If you use Homebrew to install Python 3, it will often automatically update the Python version on its own accord, and then everything breaks. With Anaconda, the Python interpreter goes into your environment.

rancid fossil
#

I have Python 3.4, 3.6, 3.7, and 3.8 on my Mac and switch between them as required. It does take a little fiddling to make Homebrew leave things alone.

#

I have Anaconda installed as well, but the conda tools don't play nice with my shell, so I generally don't use them.

astral glen
#

@rancid fossil so for stuff as basic as making an AI that detects numbers or letters
I can use anything right

#

these kind of projects intrest me the most

#

if Im being honest

#

make a car
strap a rpi

rancid fossil
#

Yes, some frameworks are easier to use than others, but most of them cover the basics

clever blade
#

Note that things move fast in this field. If something is "5 years old", there may be better techniques by now.

astral glen
#

but my laptop will die

#

as playing that game alone is just taxing on it

rancid fossil
#

Reminds me of "Rogue-O-Matic" (which is WAY more than 5 years old)

clever blade
#

Not that neural networks are always the best way to solve problems ๐Ÿ™‚

astral glen
#

I mean I'm ok with making an AI to play chess

#

that will do me just fine to get started

clever blade
#

An AI to play chess is very different from an AI that controls an autonomous car, though.

astral glen
#

hmm maybe because of possible combinations

#

but I think it will be less taxing to run chess+AI (thing??) instead of GTA V and AI

#

but yea now that I think about it

#

it does seem harder

#

ok ok comming back to topic here

#

Which pathway to go

#

like any course or youtube series you would reccomend to get me started

#

I was thinking about making a self balancing robot
get rid of PID for AI and see how that section goes

#

have seen those videos of AI learns to walk

#

just wanted to see how actual stuff would go

rancid fossil
astral glen
#

just thinking of installing linux on a VM and run basic stuff on it first and then move on
kinda dont want to install and uninstall stuff from windows again and again

clever blade
#

If you're interested in AI for controlling robots (at least in virtual environments), you could look into Reinforcement Learning, such as the OpenAI Gym.

rancid fossil
#

A YouTube search for "AI car learns to drive" yields interesting hits

astral glen
#

what would u call the Hello world of making an AI for a real robot

#

something like this?!

#

Here's one with some good reading: https:// cs231n.github.io /convolutional-networks/
@rancid fossil I'll be giving it a read

rancid fossil
#
austere patio
#

Interested in doing machine vision on legos

rancid fossil
austere patio
#

Orly....

rancid fossil
#

I'm not very far along, but even that progress is gratifying

austere patio
#

Is there a repo I can work on?

rancid fossil
#

I haven't deployed anything to a repo yet, it's pretty early days. I'm trying to build a good data set of labeled images, but it's slow going. Daniel West gives some good ideas on the subject.

#

What I have so far is basically a bunch of pieces of test code that do various pieces of the problem in various ways.

ebon epoch
#

Hello just throwing this out there, I'm trying to come up with a proposal topic on tinyml or edge computing for my master's thesis. I'm thinking about exploring self-learning algorithms on devices such as the ESP-32 (since I thought this was the most available device).

Do you guys have any suggested topics of research, or any tips/leads on this? Or on how the area is?

I apologize if this really sounds like a noob or a weird question, it just so happened that due to circumstances, I don't have anyone to talk to about this since we're like just 3 active MS students (that I know of) under my adviser (who doesn't have a lab) and these two other students have different fields than I do. My fault really for not starting and suggesting to my adviser, that perhaps we should start a research group and that I could contact his advisees if he's busy to do so.

Anyway, just thought to finally ask that somewhere since I've been reading on papers the past weeks with no one to talk to haha.

If no one replies to this that's totally fine too haha.

crisp idol
ebon epoch
#

@crisp idol thanks so much for linking this! Will check this out! ๐Ÿ˜„

fast hill
#

@ebon epoch There are some more interesting and lesser-known chips than the ESP32 if you wanted to do something more targeted specifically to TinyML. The Greenwaves GAP8 is pretty cool, as is the Maxim MAX78000, for instance.

ionic horizon
#

is this the right place to diacuss problems with the braincraft hat?

#

I am trying to go through the tensorflow lite guide and i have tried multiple times but when i try to run the Graphic labelling demo it always throws a error No module named'rpi_vision'

#

is this a known issue?

#

I have gone through the steps several times

rancid fossil
#

Sounds like you need to install that module (presumably with pip). When you installed TF Lite, were there any dependency/build errors?

ionic horizon
#

sorry just got it working for one the activate script didn't have execyte permissions

#

execute

#

but omg it was amazing

#

it recognizes a coffee mug

#

but then i pointed it at one of my dogs expecting it to say 'dog' b

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but instead it said 'Siberian Huskie'!

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which she is

rancid fossil
#

Heh, I kept getting "Schipperke" when I pointed one at my cat which confused me until I realized it was a breed of dog.

ionic horizon
#

but I always thought she was a mix with malamut (she is a rescue)

#

so the really amazing thing was when I pointed it her a 4th time it said 'malamut'

ionic horizon
#

we knew our last dog was some kind of terrier and the code identified as a west highland terrir. sorry no moreid'ing dog posts I am just amazed at what te braincraft and rpi 4 ca do

#

i have a kinda crazy project in mind. Where we live we sometimes get black bears so I am hoping to build a 'besr detector' so we are warned before we let the dogs outside or go out in the yard ourselves

#

we also get bobcats si i will train for those too

willow quarry
#

hello I'm trying to build a self driving car (just the program) so should I use yolov4?

harsh maple
#

My understanding is in order to make self driving application many modular components are needed, for the vision system one of which you could use yolo

#

Yolo isnt that great for road marking for example, that is another component

quasi pike
#

Hello all, has anyone here worked with the briancraft hat at all?

quasi pike
#

Good morning. Is anyone around to help me with a setup issue for my braincraft hat by chance?

stone dirge
quasi pike
#

I am not able to get the display to work properly

#

I followed the guide, but no video

#

The audio, buttons, joystick, dotstar and such all work...

#

so I am thinking an os update broke something?

stone dirge
#

Does the display show the console monitor on boot?

quasi pike
#

No

#

just a black screen

stone dirge
#

Di you do the "advanced" install?

quasi pike
#

Yew

#

yes

#

and I even reset my sd card and tried from scratch just in case...I am at a loss

#

The script said it completed, but no video. when doing lsmod I see the modules in place, and I have a /dev/fb1 and /dev/fb2

stone dirge
#

I don't know what to suggest -- It worked for me....

quasi pike
#

nods I was afraid of that. I'm not sure if it is defective, or I am ๐Ÿ˜›

stone dirge
#

Have you posted to the forums for "official" support?

quasi pike
#

Not yet, I was hoping someone had my experience and it was something silly. I've had good success in the past asking here

#

A lot of which was from you in fact ๐Ÿ™‚

stone dirge
#

Wish I had something to offer. Probably best to post to the Forum so thay can assess if it is defective.

quasi pike
#

nods

stone dirge
#

Good luck!

quasi pike
#

it is referenced by the one you linked

stone dirge
#

Yes, that is the right one - the other is for gettin the tensorflow demo doing, but that on is the right place to start.

quasi pike
#

My pi 4 is only 4Gb...does it require the 8gb version?

stone dirge
#

No -- Mine is 4Gb as well

#

when you plug it in , does the backlight come on? mine does then when it boots, I see the console login prompt

quasi pike
#

Yes, the backlight comes on, but it is a black screen

#

No console, no nothing

#

when trying the camera test after it is also blank

stone dirge
quasi pike
#

Yeah, mine doesn't do that unfortunately..and, STL? ๐Ÿ˜›

stone dirge
#

STL?

quasi pike
#

For that case. It is 3d printed no?

stone dirge
#

I don't have a printer -- but have been pleased with "print-a-thing".

quasi pike
#

I have an Ender 3, it comes in handy for printing cases and such

stone dirge
#

nice! Some day I'll take the plunge.

#

I have too many toys as it is!

quasi pike
#

Well, let me just say if price is what's stopping you, they're only around 200 dollars now

#

But, they make you spend more as you see the next shiny upgrade ๐Ÿ˜›

stone dirge
#

Yes - that is amazing. I'm just not ready to invest the time into owning one. yet

weak oyster
quasi pike
weak oyster
quasi pike
quasi pike
willow quarry
#

Is there a way to merge multiple TFRecord files?

trim badger
#

I got the braincraft display working, but I did have to use 270 instead of 180 for the display orientation to face me:

sudo python3 adafruit-pitft.py --display=st7789_240x240 --rotation=270 --install-type=fbcp

wise wren
#

anyone cooking up a braincraft hat with a TPU?

agile rapids
finite yoke
#

i have the new mac m1, and ive been trying to install tensorflow. i was able to download it into an environment through terminal using the apple modified tensorflow, but i need to import it into xcode. does anyone know how to do that? or has been able to do it on the m1? i keep getting errors, and idk what else to do. thanks!

rancid fossil
#

Hmm, are you using it with Python? What errors are you getting?

finite yoke
#

it just says that tensorflow doesnโ€™t exist

#

iโ€™m trying to import tensorflowlite

rancid fossil
#

You may need to install a different package

hybrid kindle
#

What would be some good ways to learn about/work with RNNs(Recurrent Neural Networks)?

muted laurel
#

Read Karpathy, then Chollet.

rapid zealot
#

I have an idea for something that I'm assuming is very simple, but i hoping for some quick pointers on where to start. i have a use case where i need to know where I am at in a particular song that can be heard on a mic. Think Shazam with a position. The song will be known but will need to be listened for and identified. The plan is to trigger different things based on the time of the song playing. Any pointers would be very appreciated...

clever blade
#

Not sure why you're assuming this is very simple. ๐Ÿ˜‰

rapid zealot
#

i guess the reason why i thought it was simple is because it would be like Shazam for only one song. Like 'Not Hotdog' ๐Ÿ˜†

clever blade
#

I think the approach would need to be quite different. It depends on what kind of song it is and when you want to trigger certain events, but a basic sound classifier might work.

tawdry garden
#

hi ummm yeah I'll be totally honest

#

I have an ML assignment

#

and I'm comletely out of my depth

#

and so I'm going to shamelessly ask for help

#

by the way, hi everyone. Hope everyone is doing well

#

๐Ÿ˜†

#

so I'm supposed to use python

slender turtle
#

@tawdry garden What are you trying to do?

tawdry garden
#

@slender turtle I'll explain in a second

#

are you familiar with polynomial feature regression?

slender turtle
#

I may have done something with it at some point not not very familiar

#

That being said from by quick look it doesnโ€™t seem like too complex

#

@tawdry garden Do you know what libraries you are supposed to use or do you have to implement everything manually?

tawdry garden
#

so what exactly does r2 mean?

#

yeah I made some progres...

#

so I have a question where it asks me to justify whether or not there is a nonlinear association

#

between each predictor and label

#

trying to undestand what this mean

#

does t his just mean that the higher

#

r^2 the more likekly the model explains it

#

so if the model is polynomial in nature

#

then

#

we can say that it has a polynomial relationship

slender turtle
#

The R^2 seems to be how accurately the polynomial fits the data

tepid herald
#

Hello everyone! I have a question... Can Feather M4 Express support speech recognition(or any machine learning ai project) ????

#

Is there a tutorial, because I cant find it๐Ÿ˜ซ

clever blade
#

The ATSAMD51 should be powerful enough but I'm not sure if there are special things you need to do to make it work on the Feather M4 Express.

tepid herald
#

Ohh

#

Thank you very much!

#

Yeah, ther is the pybadge

#

And it uses atsamd51j19

#

And feather m4 uses atsamd51j19a

#

I thought it would also work on it, but wasnt sure

clever blade
#

Even if something like TensorFlow doesn't work on it, you can still implement it yourself. I have some ML code running on an Arduino Uno, for example.

tepid herald
#

Wow

#

How did you do it?

#

There is no good tutorial on internet

#

Only for nano ble

tepid herald
clever blade
tepid herald
#

Thank you very much๐Ÿ˜… ๐Ÿคญ

marble python
true hamlet
#

Hey, I just got a Jetson Nano 2gb and a raspi cam to go with it. I have 0 experience with machine learning and just decided jump in. What are some good starting projects?

clever blade
#

Object detection is fun: it draws bounding boxes around objects that the model has been trained to recognize, such as bananas etc.

true hamlet
#

Right on, I'll look into that first. Thanks!

true hamlet
#

can I feed multiple videos and get multiple outputs saved with segnet so I don't have to start it manually for a number of small clips?

hallow quarry
#

Good evening guys, how are you?

I have a problem with my Naive Bayes algorithm for filtering Spam Emails. Can anybody help me?

Thanks!

fast hill
abstract swallow
#

Hi everyone. I am trying to implement Tinyml on Adafruit Feather nRF52840. The model sketch is based on the Magic Wand sketch issued by TensorflowLite library.

The model was uploaded successfully for one day, but for the following days I got several problems like โ€œPort not correctly ejectedโ€, no data can be received on the port, and unable to upload the sketch. Let me know if any of you may encounter the same problems and have some clues about it. Thanks for your kind help!

clever blade
#

Is the sketch writing a lot of data to the serial port?

abstract swallow
# clever blade Is the sketch writing a lot of data to the serial port?

Thanks for your quick reply! Yes. The sketch writes lots of data, as we are collecting IMU data.
The error message is "Failed to upgrade target. Error is: No data received on serial port. Not able to proceed."
We are also wondering whether the hardware of Adafruit Feather nRF52840 can support ML models, as the Tensorflow lite website doesnt include Adafruit Feather nRF52840 as the supported device then.

clever blade
#

It's the same chip as the Arduino Nano 33 Sense BLE so I'm sure it will work.

#

However, if you're sending out lots of data on the serial port, your computer may not be able to connect to it. I don't know anything about the Adafruit Feather nRF52840 board but perhaps you can put it into bootloader manually by double-clicking the reset button (like you can with Arduinos)?

abstract swallow
tribal meteor
#

i'm training a new wake word for a little open source project and could use some extra voices for training data.

if you're into it. use the voice note function to record yourself saying "hey, russell" 10 times (one long recording) , like you would say "hey, siri" or "hey, google" and send it off to me. thanks in advance ๐Ÿ™‚

tepid herald
tribal meteor
#

i'm using a raspi, using an open source project called mycroft

tepid herald
#

I wanted to make the same with a feather m4

#

But i dont se too much documentation

weak oyster
#

so i just want to know if this would work. so im building a candy wrapping machine for my business with 5 adafruit motor control boards and there running around 8 steppers. design aside i was wondering if i could implement tensor flow or machine leanring into my machine. I have multple sensors for homing and yea. im very new to this stuff

fast hill
#

This sounds of a case of: "I have a problem. I know, I'll use ML for it! ... Now I have two problems."

slender turtle
serene torrent
#

You don't always want to add something new to the situation, or else more problems XD

clever blade
#

If you want to get investors you always need the latest hot thing. Which is why everything has ML in it now.

wicked parrot
clever blade
#

Just add a linear regression somewhere and you're good to go.

wicked parrot
#

Iโ€™ll just add it to the unit tests

#

Iโ€™ll get the intern right on it

#

Which is funny because I do have an intern on my team and I had to carve out the unit tests from my task for the intern to have something to do

#

Also, apparently a lot of schools are not teaching git anymore

#

I guess machine learning is learning how to determine if I should push code or not and automatically do it for me

uncut otter
#

i kind of taught myself python and linux and have made a tflite model that detects different lego for a lego sorter

#

its amazing how accessible this is these days

#

that was all in about 2 weeks to

#

so many youtube tutorials and good pieces of code available

wicked parrot
#

My issue is more of a time constraint than a learning constraint.

serene torrent
#

Today we can easily build robots to sort Lego, 20 years ago not everyone even had a computer...

wicked parrot
#

Yeah

#

2001 was a wild time

serene torrent
#

Indeed

wicked parrot
#

Dotcom bubble, 9/11

#

The housing crash after the dotcom bubble

serene torrent
#

Crazy times

#

90s were pretty weird

wicked parrot
#

Hard to believe it was 20 years ago that I was in 3rd grade

serene torrent
#

Lol

cosmic kelp
serene torrent
#

I think I was on a Pentium III? Forget what was new then

serene torrent
wicked parrot
#

My parents had a gateway 2000 from 1998 in 2001

#

They bought it new in 1998

#

Had a speedy 56k modem lol

serene torrent
#

Stats supposedly from census data, probably close enough

#

US numbers

wicked parrot
#

Weird, in 2010 still only 77% of us households

cosmic kelp
#

Hmm. I guess I was in that 8.2% then. Had that first Mac and have had something ever since. Actually, a MacPlus.

serene torrent
#

My house has had computers for the longest time

#

Now computers outnumber people in my house like... 14:1

clever blade
#

The funny thing is that ML goes back pretty much to the beginning of computers.

#

And some of the techniques that are considered to be ML go back 100s of years.

serene torrent
#

Yup! Not a new thing, just newly exploding

clever blade
#

Although a lot of the recent achievements really have been breakthroughs.

serene torrent
#

Indeed

#

Same sort of thing happened with electricity -- conceptually was around for several hundred years, and then exploded in the last couple centuries

clever blade
#

Many products that claim to do ML really use simple techniques though. Basically replace a heuristic by a trained model. Not everything is fancy deep neural networks.

serene torrent
#

Yee

cosmic kelp
#

And a lot of the stuff that does extremely fancy AI (with pedigrees going back to the 70s and costing hundreds of millions in research dollars) is pretty useless.

#

E.g., CyCorp. I did a fair bit of work with their ontology, very cool and amazing at some level, but on the whole (sadly) kinda useless. They of course still sell it for huge bucks.

#

First saw it in action at SRI in 1979. Still around and still for sale.

rancid fossil
#

@uncut otter I'm working on the same notion: thinking a RasPi with a camera and some servos to direct bricks into chutes. I have a basic model up and running but need more training data and I'm building a brick hopper and conveyor.

true hamlet
#

I posted this in projects, but it might be better here: I'm using a jetson nano with PyTorch, when trying to use train.py i get an error saying no files in the val directory.
Does anyone have experience with this, and what is the purpose of said folder?

true hamlet
# true hamlet I posted this in projects, but it might be better here: I'm using a jetson nano ...

This video explains it around the 6minute mark. This stuff is neat, but the Jetson tutorials have me feeling like a scavenger hunter hopping through both the videos and written guides to get the whole picture.

https://www.youtube.com/watch?v=sN6aT9TpltU

Learn how to train image classification models with PyTorch onboard Jetson Nano, and collect your own classification datasets to create custom models.

Hello AI World - https://github.com/dusty-nv/jetson-inference
Jetson AI Fundamentals - https://nvidia.com/jetson-ai-fundamentals
NVIDIA Developer Forums - https://forums.developer.nvidia.com

โ–ถ Play video
clever blade
#

The "val" folder should contain a set of validation images, which are like training images except it should be images you did not use for training. The validation set is used to make sure your model works OK on images it has never seen before.

true hamlet
#

What are differences between the different model choices (such as AlexNet, GoogleNet, ResNet?) Does this refer to a format, or just pre-trained info?

rancid fossil
#

A little of both. The way these models are built is a network is defined (with varying numbers of different kinds of layers), then it is trained up on a corpus. So a given model is a particular network trained on a specific corpus. Many of them are trained on ImageNet.

#

The tradeoffs are generally model size/complexity and accuracy, and some are better at some tasks (like segmentation), others at classification, etc.

#

A common use case is for "transfer learning" where you take the pretrained model, swap out the last layer (or few layers) and retrain those on your specific data. This allows you to leverage the built-in learning embedded in the model, so you can train up a custom one without having to assemble a huge amount of data and spend enormous resources training.

#

Note: models can differ as to the form of data they take as input: many of them are configured for 224x224 pixel images with RGB color, but there are lots of other possibilities.

true hamlet
clever blade
#

Usually the training scripts will do the image conversion for you.

#

Note that AlexNet and GoogleNet are obsolete architectures by now.

#

Usually (but not always), the larger the model, the better the results. ResNet-50 gives better results than ResNet-18, for example.

true hamlet
#

Assuming everything else is the same, the larger the suffix will potentially increase accuracy while also (presumably dramatically?) increasing training time?

rancid fossil
#

They're pretrained, so the training time isn't a problem. A well designed net will outperform a poorly designed one, but most of the ones in use these days are well designed, so in general, large ones will outperform small ones, but of course they take more memory and CPU to run.

true hamlet
#

I meant when transfer learning, I should have clarified sorry

rancid fossil
#

Normally you only train the last layer (or few layers), and the rest of the network already "knows" how to recognize stripes, shapes, colors, etc.

#

Since you're only training a small part, the size of the rest of the network isn't a particularly large factor in training time.

clever blade
#

It also depends on the size of your dataset. If you have relatively little data, a smaller model usually works better (because a big model will simply remember your dataset rather than learn anything from it, i.e. overfitting).

mint pollen
#

I want to use ML for two accelerometer data heavy projects.

  1. impact detector for a fencing mask that can classify movements as not impacts and classify impacts on direction and severity. This would be for scoring and safety.

  2. sword helper that would attach to a training sword for a variety of purposes: the other side of the impact detection system that could assess whether the sword hit another sword or the ground or a mask/jacket, and a solo-trainer "coach" that can assess important characteristics of practice like edge alignment, acceleration curve, etc.

This seems like one of those things that would be possible but a pain to do programmatically (and I did for my senior project years ago), and ML seems a good fit based on the examples from TensorFlow Lite I've seen.

This is my first time messing with this sort of stuff. Any ideas on how to collect a good training dataset, how big it should be, and what kind of learning approach to take? A neural network sounds right, but I'm not sure how supervised I should go with it or any of those other details.

I have access to a lot of people skilled with swords, so no worries there.

rancid fossil
#

It's an interesting problem. Ultimately, you'll need supervised learning, with a labelled data set, but you might be able to use unsupervised learning to help divide the dataset into categories.

#

Since the problem doesn't map to the usual ones for which pre-trained models are available, you may not be able to take advantage of transfer learning, so you'd need a pretty big data set.

rugged obsidian
#

( creating a dataset sounds like fun though. You get to hit people with swords. for science. )

robust vapor
#

And not-people. Have to train on the not-people, too...

sharp juniper
#

Suggestions:Put the accelerometer on the inside of the bell, not the mask. For epee, anywhere counts other than the floor, so use the body cord to eliminate floor touches. For foil, the electronic scoring system already generates valid touches, so again, use the body cord and the accelerometer.

#

For saber, same as foil. Accelerometer will need to distinguish point touches from blade touches. ML will help by training against an active plastron on a dummy.

clever blade
#

You probably also don't need a neural network for this. In general, you'd start by training a simple baseline model on the data (such as a logistic regression). Often you'll find that this already gives good enough results. In any case, it's an iterative process: gather training data, train a model, tweak the model, gather more / different training data, train the model again, experiment with a different model design, gather more data, and so on.

mint pollen
#

Oh, I should clarify, the swords I use are two-handed, not epee or foil or sabre. So, choppy and stabby. And slice-y, and I think I could measure that one too, which is part of why this is exciting.

#

3 types of wounding strikes, 4 quadrants/direction vectors, 2 edges of the blade = 24 categories I can categorize for the learner.

sharp juniper
#

Gotcha. Instead of making a simple task complex youโ€™re trying to make a complex task simple.

neat owl
#

You might want to look at random-forest. It's better with a smaller training dataset, plus it's a classifier that gives a "confidence".

crimson wagon
#

I am trying to get tensorflowlite running on Clue, I have seen lots of talk from 2019 onwards but little info. Is there a writeup?

#

or at least cookbook-ish pages

#

everything I "fixed" just gives 2 new errors

#

arduino compile errors galor

maiden pulsar
#

I've been having a lot of fun with the VQGAN+CLIP technique that's really popular right now. yesterday I built a little discord bot that lets you generate images either from just text, or a provided image + text prompt

#

right now it's just running on my desktop, so it maxes out my GPU for a few minutes for each image. does anyone have any suggestions for a cheap hosting solution for GPU stuff? i'd love to be able to move this somewhere where it can run all the time

serene torrent
#

I'll run it and charge you processing time :P

rocky swan
#

does anyone have some experience with pullet? I need some help ๐Ÿ™

slow depot
#

Is it bad if I put a PDF here with some questions(about 25 questions) about the Adafruit Machine Learning Kit and Microsoft Lobe? (My questions)

mint pollen
#

Trying to figure out the initial data-gathering stuff for the "Smart Sword v2.0." The magic_want_model_data.cpp file has this helpful tidbit:

// Automatically created from a TensorFlow Lite flatbuffer using the command:
// xxd -i magic_wand_model.tflite > magic_wand_model_data.cc
// See the README for a full description of the creation process.

But the readme for the Adafruit TensorFlow Lite Helper Library where the file is found doesn't say anything about the data creation process.

I've tried following this example and replacing the external sensor values with the Circuit Playground built-in LIS3DH calls: https://www.survivingwithandroid.com/arduino-tinyml-gesture-recognition-with-tensorflow-lite-micro/ ; but I'm confused as to why it is calibrating like it does and if that's what I want to do. As far as I can tell, it records the "neutral" position (starting position) and uses that to adjust all the other values. However, because gravity, if it is oriented any other way it will register as movement. I suspect it has something to do with the MPU6050 being a gyro and accelerometer? So I'm going to go back to how I did this before on my non-ML system and just use a threshold of acceleration and use the acceleration delta rather than the raw values.

tl;dr: I'm not actually sure whether I'm doing the data-gathering for the model I want to build right, but this has actually been pretty fun all things considered.

vocal stone
#

Does anyone know about the bme688 Bosch gas sensor. Does the adafruit (680) library have any ai support? Somehow the bme688 is set up to perform an algorithm of machine learning to match a gas.

I bought an huzzah esp32 feather, a bme688 feathering and several adafruit bme688 sensors.

Any pointers for what to read?

What I know so far:
A huzzah feather firmware by Bosch controls an 8x bme688 sensor wing to get a lot of resistor readings at different temperatures when identifying a gas.

AI software compares a positive & a negative test array to produce code that will scan for a positive hit rapidly. (I am assuming N different gasses can all be sniffed by the generated algorithm).

So far, that algorithm is run via the 8x bme688 sensor board with promises of being able to run via the cheaper 1x sensor by adafruit.

ripe night
vocal stone
#

Thanks!

vocal stone
#

A primary use of the bme688 sensor is to detect gasses against baseline measurements.

The BSEC2.x library drives the bme688 to perform measurements.

It would be nice if that library can be added when the bme688 library is added AND it be callable via python.

Otherwise, reading out a resistance value is pretty meangless [to me].

A user can duplicate the AI work done by Bosch but that is a difficult path for someone that is thinking they just want to detect a banana.

sleek fable
#

Hey guys

eternal ravine
#

What's the best way to learn more about ML and Python??

rancid fossil
#

Heh, define "best". I'm doing it by building a Lego brick sorter.

clever blade
#

Introduction to Machine Learning with Python by O'Reilly teaches both.

eternal ravine
#

Is there a good website to find ML python code on besides Kaggle?

rancid fossil
clever blade
#

That book I mentioned actually has a lot of code in it. It's like a more professionally done version of a typical online tutorial.

glad pewter
#

I have finally thought of a useful project, but now how to create. Input device, I need to bulk load photos. Should I look at a scanner or the tenserflow hat? Is there away to build my own scanner or is the hat fast enough?

true hamlet
#

Hey I'm trying to train my Jetson Nano on classification. Under the validation folder, what kind of pictures should I be putting?

#

or are they just images for the train folder to bump heads against and train the model, so to speak

fast hill
#

I believe the validation set is to test whether the model has been well-trained or not. If it gets the training set correct but fails on the validation set, then it hasn't generalized the classification enough to work correctly, instead just keying on some random specific details of the training set to fake the answers.

true hamlet
#

Okay, I think I am following

robust phoenix
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Hello everyone, I have a dataset with audio files with .wav extension. I want to output a cpp(unsigned char) from these audio files. I don't know both pyhton and tensorflow. I created a copy-paste algorithm with my research. First of all, I modeled my dadasets with TensorFlow speech recognition. Then I translated this model into Tensorflow lite. Then I tried to get cpp output. And I got no results. Is the path I followed correct to achieve the result I want? Or is there another way I can follow?

rancid fossil
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I'm not sure what you mean by cpp output? Something like the WAV data in hexadecimal values in a C array?

robust phoenix
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I am using esp32. I have a dataset with .wav files. I want to make an Arduino code out of them.

robust vapor
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Make an Arduino code with a dataset? Do you mean importing data parsed from wav files?

#

Code is a set of commands, and data is just raw or formatted information.

robust phoenix
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I have an ESP32 board with microphone. I want to generate an Arduino code from the datasets(rabbit, true,wrong vs) I have. For example, when I model the dataset with "rabbit" sounds and say rabbit into the microphone, I want it to print "rabbit" on the screen.

muted laurel
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Maybe Shawn can help. https://youtu.be/dU01M61RW8s

In this tutorial series, Shawn introduces the concept of Tiny Machine Learning (TinyML), which consists of running machine learning algorithms on microcontrollers.

In this episode, we create an (as simple as possible) Arduino sketch to load our TensorFlow Lite model file and run inference. The model is used to predict values of a sinewave, whic...

โ–ถ Play video
steel parcel
#

Greetings!
Where would you start from to develop a solar panel system and storage, which could produce enough and necessary energy given a certain type of lifestyle? so based upon your life needs "lifestyle" / " cost of living ", can give as a result an average of what you would need to carry out a system that can make you live without paying the bills.

steel parcel
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oh sorry

#

where should be the right one?

cosmic kelp
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Well, does Adafruit sell any solar panel systems?

#

The biggest they sell is a 9 watt panel. That's hobbyist size. If you're talking about one for your house you might try a forum or Discord server devoted to solar living or something. If you really want to ask the Adafruit community you might try under #general-tech but your results are going to be pretty random if you're looking for solar specialists.

whole birch
# steel parcel Greetings! Where would you start from to develop a **solar panel system and sto...

Yeah, probably not the channel for it, but; 1) determine the energy consumed for your lifestyle, eg; "Watt-hr" - an easy way to find this is your electric bill 2) use some tools to estimate your solar viability, eg; https://sunroof.withgoogle.com 3) dive into the timeseries of solar vs. time - you'll need a battery large enough to get you through the lowest point - but it also has charge history associated with it, and may not be fully charged at the start of that lowest point.

Enter a state, county, city, or zip code to see a solar estimate for the area, based on the amount of usable sunlight and roof space.

tepid herald
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Hi! I am trying to use tensorflow micro in a normal esp32(nodemcu) with a normal microphone(max4466 with analog output) and I cant find any tutorial. Everyone uses I2S microphones but adafruit shows a tutorial with a max4466 for its pybadge(that is why I think it is possible). Tensorflow for ESP32 library is not complete for this case. Can someone help me to figure out how to use this type of mic in the tensorflow microspeech example? Thanks!!!

devout sluice
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i'm trying to follow the tensorflow for microcontrollers hello world guide, but i keep getting the error make -f tensorflow/lite/micro/tools/make/Makefile hello_world_test. how do i fox this? it appears when i run the test makefile

rancid fossil
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That appears to be a make command, not an error

devout sluice
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sorry, had the wrong thing copied. it was a search for a /google/ directory, which didn't exist

#

find: โ€˜../google/โ€™: No such file or directory was the exact error

rancid fossil
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That's looking for a google directory in the parent directory, and it is (apparently) not there

devout sluice
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how do I fix it?

rancid fossil
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That's a good question. Presumably there's some other files that need to be fetched and installed in the proper place, but I'm not familiar enough with that guide to say for sure.

tepid herald
rancid fossil
tepid herald
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Thank you for responding, it gives me this file instead of creating a a .pb file

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Foto de Arsenio

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It creates that. But when I do it with version 2.4.1 it does it correctly:

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Foto de Arsenio

rancid fossil
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Hmm, that's interesting.

tepid herald
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๐Ÿฅฒ do you know how to solve it??

rancid fossil
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Alas, I don't. My first impulse is to say "just use the version that works", but I'm guessing you want a more thorough answer.

tepid herald
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Yes haha, I need an expert... But thank you

muted laurel
muted laurel
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Okay I'll give it a try.

twilit viper
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Uh. I just came here to not ask about building the next Skynet like Dexter over here, but if I were to ditch the Google Assistant and Siri and Alexa, for something different, would Almond be a good thing to get into, or should I just roll my own with TensorFlow Lite and use a bunch of little feathers or whatever for input?

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My main gripe with the assistants, other than the fact that they constantly listen and record (fOR diAgNOstiK purRpoSSes oNLy dUh) they are also completely useless if my Internet goes out.

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Oh, I am using Home Assistant on a Raspberry Pi 4 for this, by the way.

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(and maybe this would get me into the audio side of things, building smart speakers)

rancid fossil
twilit viper
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I'm wondering if I could scavenge a few of my Artemis-based feathers and turn them into... Something...

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Basically something that isn't double the cost of a an Echo Dot or the little Google thing, whatever it's called.

vernal moss
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There's also um.... bugger. I'm blanking on the name. Hold please.

twilit viper
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I don't really need it to play music, per se, I can redirect that over to my home entertainment system.

vernal moss
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Mycroft!

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No idea if it would do anything you want.

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But it's open source.

twilit viper
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I'll look at it! Thank you.

vernal moss
twilit viper
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Yeah, I was curious about Almond (and the Ada voice assistant for Home Assistant)

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Oh sweet, I'll check that out!

vernal moss
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Hmm evidently they're sold out and the images are on Debian Jesse. There are pre-orders for Mark II, but it's been a real slog for them to get going. (I have a friend who has a ton of their hardware, and did a presentation to our local user group on it. I ran to him to find out the name when I couldn't remember.)

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So... caveat. But it still might be worth looking at.

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It still works and you can install it on RPi/Linux to try it out.

twilit viper
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The main thing I see is that it requires Pi 3/4. I mean. Good luck finding like 3-4 of those to replace my Google Assistants.

vernal moss
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Oof yeah.

twilit viper
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Yeah, that's why I was hoping for something that'd run on something with tensorflow lite or similar

vernal moss
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Fair enough. Well, I evidently can't help you there. ๐Ÿ˜„

twilit viper
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You helped! This gives me ideas.

vernal moss
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Oh good!

twilit viper
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I'm going to have to do some testing later tonight. I'll keep y'all updated.

vernal moss
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Thanks!

split crater
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I just built the coolest machine learning program in python, it identifies your age and address validation against USPS API and the DMV for a website login purposes

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for account signups to stop catfishing and scamming and botting

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now I just need to learn how to use flask and ue

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vue

twilit viper
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there's a bare minimum, yet fully functional, Flask app

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And Vue is so... last decade. You should check out Svelte.

hazy bane
# twilit viper Uh. I just came here to not ask about building the next Skynet like Dexter over ...

This tutorial shows how to build your own digital virtual assistant in Python, complete with voice activation plus response to a few basic inquiries.

This article is about creating a voice assistant using python programming.

twilit viper
spring drift
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I use https://www.adafruit.com/product/4757 + mozilla deep speech, but it looks like deep speech was abandoned, so I'll need to find another speech to text converter, and it requires a raspberry pi 4 which you mentioned is a bit hard to find

twilit viper
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Or are the Raspberry Pi and Jetson GPIO headers not comparable?

eternal ravine
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I highly recommend

muted laurel
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we have been a dozen people

mossy garnet
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Hello guys would someone mind helping me to take a course on computer vision and image processing fundamentals. Has anyone studied the course kindly share resources and ur experience bcas I'm finding difficult

tepid herald
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On youtube murtazas workshop is very helpful

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And shawn hymel also

eternal ravine
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Not the most active channel

rancid fossil
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My machine learning project is not progressing rapidly

pliant crescent
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Wondering if anyone has any suggestions on where to get started on ML. I've got a pi and camera taking pictures of my bird feeder, and I'd like to attempt to pull out images that actually have birds in them. I have no idea where to start.

wicked parrot
lapis island
pliant crescent
lapis island
twilit ravine
fast hill
#

I have a large corpus of scanned pages of my own handwritten notes. Does anyone know of a tool that would use a language model to train an OCR engine specifically on my handwriting to annotate those pages?

rancid fossil
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I remember seeing some projects for handwriting recognition, but they were simple demo ones that just recognized digits. While you could probably build one of those into a handwriting engine optimized for your handwriting, it would be a fair amount of effort. Hopefully someone else is aware of something that's closer to your use case.

fast hill
weak oyster
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google/bing voice search still doesn't recognize my English after 2 millenias...

pulsar bear
verbal eagle
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This might be something to see if an FOIA request might be able to get USPS to release their software? (Much like what happened with the NSA's Python training.)

wide bone