Machine Learning A-Z - Udemy course
- Part 1 - Data Preprocessing
- 02 - Data Preprocessing
- Part 2 - Regression
- 04 - Simple Linear Regression
- 05 - Multiple Linear Regression
- 06 - Polynomial Regression - Curve fitting
- 07 - Support Vector Regression (SVR)
- 08 - Decision Tree Regression
- 09 - Random Forest Regression
- Part 3 - Classification
- 12 - Logistic Regression
- 13 - K-Nearest Neighbors (K-NN)
- 14 - Support Vector Machine (SVM)
- 15 - Kernel SVM
- 16 - Naive Bayes
- 17 - Decision Tree Classification
- 18 - Random Forest Classification
- Part 4 - Clustering
- 21 - K-Means Clustering
- 22 - Hierarchical Clustering
- Part 5 - Association Rule Learning
- 24 - Apriori
- Part6 - Reinforcement Learning
- 27 - Upper Confidence Bound
- 28 - Thompson Sampling