Mathematics for Artificial Intelligence

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Related Topics

• Python Basics
• GitHub Copilot
• Azure AI

Table of Contents

• Foundations
  • Getting Started
• Linear Algebra
  • Vectors and Vector Spaces
  • Matrices and Matrix Operations
  • Eigenvalues and Eigenvectors
  • Singular Value Decomposition (SVD)
  • Principal Component Analysis (PCA)
• Calculus
  • Limits and Continuity
  • Derivatives and Differentiation
  • Partial Derivatives and Gradients
  • Chain Rule and Backpropagation
  • Integrals and Integration
  • Multivariable Calculus
• Optimization
  • Gradient Descent
  • Stochastic Gradient Descent (SGD)
  • Convex Optimization
  • Lagrange Multipliers and Constraints
  • Second-Order Optimization Methods
• Probability and Statistics
  • Probability Theory Basics
  • Random Variables and Distributions
  • Bayes’ Theorem
  • Expectation, Variance, and Covariance
  • Common Probability Distributions
  • Hypothesis Testing
  • Maximum Likelihood Estimation (MLE)
  • Bayesian Inference
• Information Theory
  • Entropy and Information
  • Cross-Entropy and KL Divergence
  • Mutual Information
• Graph Theory
  • Graph Fundamentals
  • Graph Neural Networks (GNNs)
• Discrete Mathematics
  • Logic and Boolean Algebra
  • Combinatorics and Counting
  • Set Theory
• Numerical Methods
  • Numerical Stability and Floating Point
  • Monte Carlo Methods
  • Fourier Transform
• Mathematical Foundations of Deep Learning
  • Loss Functions
  • Regularization Techniques
  • Activation Functions
  • Universal Approximation Theorem

# 1. GETTING STARTED