Hands-On Machine Learning

Learn practical machine learning implementation through a comprehensive 5.5-hour course covering essential algorithms and techniques. Work through a complete machine learning project from start to finish, then dive into classification methods and model training fundamentals. Master support vector machines for complex pattern recognition, explore decision trees for interpretable predictions, and understand ensemble learning methods including random forests for improved accuracy. Discover dimensionality reduction techniques to handle high-dimensional data efficiently, and conclude with unsupervised learning approaches for finding hidden patterns in data without labeled examples.

Syllabus

Hands on Machine Learning - Chapter 2 - Full Machine Learning Project
Hands on Machine Learning - Chapter 3 - Classification
Hands on Machine Learning - Chapter 4 - Training Models
Hands on Machine Learning - Chapter 5 - Support Vector Machines (SVM)
Hands on Machine Learning - Chapter 6 - Decision Trees
Hands on Machine Learning - Chapter 7 - Ensemble Learning and Random Forests
Hands on Machine Learning - Chapter 8 - Dimensionality Reduction
Hands on Machine Learning - Chapter 9 - Unsupervised Learning