Beginner to intermediate reference
Machine Learning Study Notes
A structured reference covering mathematical notation, dimensions, algorithms, worked calculations, implementation logic, common mistakes, and small interactive figures. No previous machine-learning knowledge is assumed.
Begin with Lesson 1: Tensor →
How these notes are organised
Definition, derivation, example and implementation
Each topic is written as a self-contained set of study notes. It begins with intuition, then introduces precise terminology and notation, follows dimensions through the operation, works through a numerical example, and ends with limitations and a short knowledge check.
1Start with a familiar analogy before introducing terminology.
2Follow the information: what enters, what happens, what leaves?
3Use a tiny numerical dry run and an interactive experiment.
4Learn the common mistake and answer one self-check question.
5Only at the very end, connect the general idea to the GAN project.