Table of contents

• Introduction to Machine Learning
• Zero-Order Optimization Techniques
• First-Order Optimization Techniques
• Second-Order Optimization Techniques
• Linear Regression
• Linear Two-Class Classification
• Linear Multi-Class Classification
• Linear Unsupervised Learning
• Feature Engineering and Selection
• Principles of Non-linear Feature Engineering
• Principles of Feature Learning
• Kernel Methods
• Fully Connected Neural Networks
• Tree-Based Learners