You trained your first model. You check the metrics. R2 is approaching 0.99.

What does a typical beginner do? They rejoice, run to the client demanding a bonus, and ask to deploy this miracle to production.
What does an experienced person do? They go gray, nervously drink coffee, and look for where they have a data leak.

In the real world, perfect metrics are almost nonexistent. If your model predicts everything, it means it's cheating. The model should work on new, unseen data. To do this, you need to understand the logic of validation, not just copy-paste train_test_split out of habit.

These are the things we will study in the new season of the ML Master Group. The program includes:
🟢 5 live sessions: from the very basics of machine learning to building and validating basic linear models.
🟢 1 session — team practice. Stop just watching lectures. You will solve a practical problem in teams, and then we will all review the results together (and see who messed up where).
🟢 Recordings and my code files, of course, remain with you. Take them and use them as a cheat sheet at work.

🗓 The first live session is tomorrow at 11:00 Moscow time.

For those who take a long time to get started — the doors are still slightly open. If you're interested, write to me in private messages @obulygin91 ◀️