Foundations

Timeless theoretical foundations. Notes here answer: why does this work mathematically?

Sublayers

Math

Mathematical theory underpinning ML and data science.

• math — top-level math index
  • calculus — differentiation, integration, series, ODEs
  • linear_algebra — matrices, linear systems, vector spaces, eigenvalues

Deep Learning Theory

Theoretical foundations of neural networks and optimization.

• deep_learning_theory — full index
  • Key notes: backpropagation, gradient_descent, adaptive_optimizers, batch_normalization, weight_initialization

Statistical Learning Theory

Theory of generalization, model selection, and ML strategy.

• statistical_learning_theory — full index
  • Key notes: bias_variance_analysis, evaluation_metrics, data_splits_and_distribution