The Purpose of Train-Test Split in Machine Learning | How to Correctly Split Data? скачать в хорошем качестве

The Purpose of Train-Test Split in Machine Learning | How to Correctly Split Data?

🔥 In this video we discuss one of the most important concepts in machine learning called: train-test split. Through clear visualizations, we explain the significance of splitting the data into train and test sets and how separate subsets should be properly used. Test data is used for final model evaluation, meaning that it should not be used in any other stage. Validation set is used for model selection and configuration, which is a topic we will talk about in the upcoming videos. 🔍 Key points covered: 0:00 - Introduction. 0:07 - What if you use all data for training? 0:35 - Why data splits are used? 0:41 - The ratio of test/train split. 0:47 - The intuition for splitting the data. 1:05 - Randomly splitting. 1:16 - Little data can be problematic! 1:35 - At what stage to do the train-test split? 1:55 - What about the validation set? 2:07 - Subscribe to us! 🔔 Don't forget to like, subscribe, and hit the bell icon to stay updated with our latest videos! 🤖 Note that we use synthetic generations, such as AI-generated images and voices, to enhance the appeal and engagement of our content. 🌐 If you have any questions or topics you want us to cover, leave a comment below. Additionally, share with your thoughts about the content, how do you think we can make them better? Thanks for watching!