Phase 02

ML Fundamentals

Phase 2: ML Fundamentals. 18 hands-on lessons building AI from first principles in the browser. Free reading; graded exercises and certificate with lifetime access.

1. What Is Machine Learning (graded)
2. Linear Regression (graded)
3. Logistic Regression (graded)
4. Decision Trees and Random Forests (graded)
5. Support Vector Machines (graded)
6. K-Nearest Neighbors and Distances (graded)
7. Unsupervised Learning (graded)
8. Feature Engineering & Selection (graded)
9. Model Evaluation (graded)
10. Bias-Variance Tradeoff (graded)
11. Ensemble Methods (graded)
12. Hyperparameter Tuning (graded)
13. ML Pipelines (graded)
14. Naive Bayes (graded)
15. Time Series Fundamentals (graded)
16. Anomaly Detection (graded)
17. Handling Imbalanced Data (graded)
18. Feature Selection (graded)