Random Forests and Regularization | Lesson 4 of 6 | Machine Learning with Python: Zero to GBMs

💻 Lecture 4 of the Machine Learning with Python: Zero to GBMs course. In Random Forests and Regularization, we learn how to use decision trees and random forests to solve a real-world problem from Kaggle. Course page: 🔗 Notebooks used: 🎯 Topics Covered - Training and interpreting random forests - Overfitting, hyperparameter tuning & regularization - Making predictions on single inputs ⌚ Time Stamps 00:00 Introduction and Recap 10:06 Random Forests 25:31 Hyperparameter tuning with random forests 01:14:30 Conclusion 01:15:40 Assignment 2 01:21:43 What to do next? 💻 Join the Jovian Discord Server: ❓ Ask questions on the Jovian Forum: 👉 Add the course schedule to your calendar: