Supervised Learning

Build ML Models with Supervised Learning

Author: AI Learning Club Team · Difficulty: Beginner · Duration: 2 hr 25 min · Modules: 28

Modules

1. Introduction to Supervised Learning (5 min)
2. Linear Regression Basics (5 min)
3. Linear Regression Advanced Techniques (5 min)
4. Logistic Regression Basics (5 min)
5. Logistic Regression Advanced Techniques (5 min)
6. Decision Trees Basics (5 min)
7. Decision Trees Advanced Techniques (5 min)
8. Random Forests Basics (5 min)
9. Random Forests Advanced Techniques (5 min)
10. Support Vector Machines (SVM) Basics (5 min)
11. SVM Advanced Techniques (5 min)
12. Gradient Boosting Basics (5 min)
13. Gradient Boosting Advanced Techniques (5 min)
14. Model Evaluation Metrics (5 min)
15. Feature Engineering (5 min)
16. Hyperparameter Tuning (5 min)
17. Bias-Variance Tradeoff (5 min)
18. Overfitting and Underfitting (5 min)
19. Ensemble Methods (5 min)
20. Applications of Supervised Learning (5 min)
21. Case Studies in Supervised Learning (5 min)
22. Project: Implementing Linear Regression (5 min)
23. Project: Implementing Logistic Regression (5 min)
24. Project: Implementing Decision Trees (5 min)
25. Project: Implementing Random Forests (5 min)
26. Project: Implementing SVM (5 min)
27. Project: Implementing Gradient Boosting (5 min)
28. Resources & References (2 min)

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