Machine Learning Brick by Brick, Epoch 1

Focusing on practical training in machine learning, this book series begins with fundamental concepts, starting with linear associative networks. It introduces a brick notation for algebraic expressions and covers essential calculus derivations and gradient descent techniques. Later sections delve into foundational topics in computer science, statistics, data science, algorithms, and data structures, ensuring a comprehensive understanding of both theoretical and practical aspects of the field.