This repo is home to the code that accompanies Mathematical Foundations of Machine Learning curriculum, which provides a comprehensive overview of all of the subjects — across mathematics, statistics, and computer science — that underlie contemporary machine learning approaches, including deep learning and other artificial intelligence techniques.
There are six subjects in the curriculum, organized into three subject areas:
- Linear Algebra
- 1: Intro to Linear Algebra
- 2: Linear Algebra II: Matrix Operations
- Calculus
- 3: Calculus I: Limits & Derivatives
- 4: Calculus II: Partial Derivatives & Integrals
- Probability and Statistics
- 5: Probability & Information Theory
- 6: Intro to Statistics