📝 Mathematical Foundations

Mathematical foundations are the tools used to describe data, models, learning, and uncertainty in machine learning.

Area	Why it matters in ML
Probability & Statistics	Describes uncertainty, data distributions, likelihoods, and model confidence
Linear Algebra	Represents data and model parameters with vectors, matrices, and tensors
Calculus & Optimization	Provides gradients and optimization methods for training models
Information Theory	Explains losses such as cross-entropy and measures distribution differences