smoky furnace
Hey everyone, I made a Kaggle notebook for the S6E5 Playground Series on predicting F1 pit stops.
It’s mainly an EDA notebook where I explored the dataset, looked for patterns, checked relationships between features, and noted some ideas that could help with modeling.
If you’re working on the competition, maybe it could be useful. Would appreciate any feedback or thoughts if you check it out.
https://www.kaggle.com/code/adwaittagalpallewar/lap-by-lap-predicting-pit-stops-detailed-eda
waxen shore
Hii
analog topaz
Anyone struggling in Consistency and want to learn together.
DM me.
indigo bridge
Hey everyone
i am consistantly trying to improve the score for the F1 pit stops compitition with the catboost + xgboost blend
but i am stuck in 0.950 zone
can someone suggest any changes about the params or any other models i can use?
tidal lion
hello, I'm guessing since it's a playground we are not keeping our solutions secret until the deadline.
I found this solution posted by someone on Linked in https://github.com/Viraj97-SL/Kaggle---F1-Pit-Stop-Prediction
looks a bit vibe coded 😉
tough scaffold
🚀 Hey @everyone!
We’re building PromptGram and aiming to reach 150 GitHub stars ⭐
If you like AI, FastAPI, microservices, or developer tools, please check it out and support the project by starring the repo 🙌
GitHub Repo: https://github.com/dewangsahuji/promptgram
Every star really helps and motivates us to improve the project further 💙