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