smai-lecture-notes

Here, you will find all the lecture notes for the Statistical Methods in Artificial Intelligence (SMAI) course offered at IIIT, Hyderabad.

Mathematical Foundations of ML

• L1: Introduction, nearest neighbour
• L2: Training and Testing
• L3: Loss Function, Linear Algebra, SVD
• L4: Overfitting, Probabilistic View
• L5:
• L6: Gaussian Distributions

Linear Models of Classification

• L7: Linear Regression
• L8: Princiapl Component Analysis (PCA)
• L9: Gradient Descent
• L10: Gradient Descent Optimizations
• L11: Linear Perceptron
• L12: Logistic Regression
• L13: Multi class classification

Non-linear models of Classification

• L14: Support Vector Machines (SVM)
• L15: Non-linear SVM and Kernels
• L16: Kernelization
• L17: Neural Networks
• L18: Backpropagation
• L19: Backpropagation-II