Milestone 2: Mathematical Foundations for AI

🟨 Milestone 2: Mathematical Foundations for AI

AI is statistical programming. This section covers the essential math required to understand how models learn and improve.

🚀 The Senior’s Intuition

• Course MATH-200: Senior Math Intuition: Connecting abstract math to real Python/ML code.

📚 Slow-Paced Deep Dives (University Modules)

• Module 1: Linear Algebra (The Grocery List): MATH-201. Vectors, Matrices, and Dot Products.
• Module 2: Multivariable Calculus (The Mountain Climber): MATH-202. Derivatives, Gradients, and the Chain Rule.
• Module 3: Probability & Statistics (The Logic of Uncertainty): MATH-203. Distributions, Bayes Theorem, and Inference.

🥅 Milestone Goals

1. Understand Dot Products as weighted sums.
2. Conceptualize Gradient Descent as a walk down an error mountain.
3. Manage uncertainty using Probability Distributions.
4. Normalize data to fit the Bell Curve for better training.