Unit 1: Vectors and Matrices
Unit 2: Linear Independence and Span
Unit 3: Eigenvalues and Eigenvectors
Unit 4: Singular Value Decomposition
Mathematics for Machine Learning
Unlock the mathematical foundations of machine learning and gain the skills to build, analyze, and optimize intelligent systems.
Unit 1: Introduction to Calculus
Unit 2: Single-Variable Differentiation
Unit 3: Multi-Variable Calculus
Unit 1: Introduction to Probability
Unit 2: Random Variables and Distributions
Unit 3: Descriptive Statistics
Unit 4: Hypothesis Testing
Unit 1: Introduction to Optimization
Unit 2: Gradient Descent Variants
Unit 3: Regularization Techniques
Unit 4: Advanced Optimization Algorithms
Unit 1: Linear Regression with Linear Algebra
Unit 2: Gradient Descent in Linear Regression
Unit 1: Mathematics of Convolutional Neural Networks (CNNs)
Unit 2: Mathematics of Recurrent Neural Networks (RNNs)
Unit 3: Mathematics of Transformers
Unit 4: Mathematics of Generative Models: VAEs
Unit 5: Mathematics of Generative Models: GANs
Unit 6: Mathematical Approaches to Explainable AI (XAI)