AI & ML · Ebook

Machine Learning: From Foundations to Deep Learning

by Shriira Press

A comprehensive, self-contained introduction to machine learning that blends intuition, mathematics, and runnable code. The book starts from the question "what does it mean for a machine to learn?" and builds steadily up to modern deep learning, including the Transformer architecture that powers today's large language models.

Contents

1. 1Preface
2. 2Chapter 1 — What Is Machine Learning?
3. 3Chapter 2 — Mathematical Foundations
4. 4Chapter 3 — The Learning Problem
5. 5Chapter 4 — Linear Regression
6. 6Chapter 5 — Classification and Logistic Regression
7. 7Chapter 6 — Optimization and Gradient Descent
8. 8Chapter 7 — Regularization and Model Selection
9. 9Chapter 8 — Decision Trees and Ensemble Methods
10. 10Chapter 9 — Support Vector Machines and Kernels
11. 11Chapter 10 — Clustering and Dimensionality Reduction
12. 12Chapter 11 — Neural Networks and Backpropagation
13. 13Chapter 12 — Deep Learning Architectures
14. 14Chapter 13 — Building Real Systems
15. 15Appendix A — Notation and Symbols
16. 16Appendix B — Further Reading