Machine Learning Foundations and Applications: A Practical Guide to Supervised, Unsupervised, and Reinforcement Learning

Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work—mathematically and computationally.

This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development.

If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts—with clarity, depth, and purpose.