#findById and getReferenceById
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<@&1004656351647117403> please have a look, thanks.
I still don't understand it very well, could you give examples?
Of course! Here are a few examples to help you understand better:
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Weather forecasting: Machine learning algorithms can analyze historical weather data, such as temperature, humidity, wind speed, and precipitation patterns, to predict future weather conditions. By training the algorithm with large amounts of data, it can learn patterns and make accurate predictions about upcoming weather.
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Spam email filtering: Email providers use machine learning algorithms to filter out spam emails from your inbox. These algorithms are trained on large datasets of emails that have been manually labeled as spam or not spam. By analyzing the content, sender information, and other features of an email, the algorithm can classify incoming emails as either spam or legitimate.
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Autonomous vehicles: Self-driving cars rely heavily on machine learning algorithms to navigate roads and make driving decisions. These algorithms process real-time sensor data from cameras, lidar, radar, and other sensors to detect objects like pedestrians, traffic signs, and other vehicles. By training the algorithm with vast amounts of labeled data, it can learn how to interpret different road scenarios and make appropriate driving decisions.
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Personalized recommendations: Online platforms like Netflix or Amazon use machine learning algorithms to provide personalized recommendations based on your previous interactions or purchases. By analyzing your viewing history or purchase behavior along with similar patterns from other users, these algorithms can suggest movies or products that you might be interested in.
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Fraud detection: Banks and credit card companies employ machine learning algorithms to detect fraudulent transactions in real-time. These algorithms analyze various factors such as transaction amount, location, time of day, spending patterns, and more to identify suspicious activities that deviate from normal behavior. This helps prevent fraudulent transactions and protect customers' accounts.
These examples showcase how machine learning is applied in various domains to solve complex problems by leveraging large datasets and training models to make accurate predictions or decisions based on patterns in the data.
findById returns the optional. If id is present then it will return optional of id else return empty optional.
getReferenceById will throw exception if the item with that id is not present in the db.
Optional<T> findById(ID id);
This is the syntax of findById
T getReferenceById(ID id);
this is the syntax of getReferenceById
You can follow this if you like:
https://www.baeldung.com/spring-data-jpa-getreferencebyid-findbyid-methods