📄️ Basics
Basic Derivatives
📄️ Linear Algebra
This guide covers the essential linear algebra concepts needed for machine learning, including vectors, matrices, matrix calculus, and their applications.
📄️ Probability and Statistics
This guide covers the essential probability and statistics concepts needed for machine learning, including distributions, expected values, Bayes' theorem, and maximum likelihood estimation.