/NPTEL-Intro-to-ML

This repo will contain PPT slideds used by the professor in the NPTEL course Introduction to machine learning

NPTEL-Intro-to-ML

This repo will contain PPT slideds used by the professor Sudeshna Sarkar in the NPTEL course Introduction to machine learning.

COURSE LAYOUT

Week 1:

Introduction: Basic definitions, types of learning, hypothesis space and inductive bias, evaluation, cross-validation

Week 2:

Linear regression, Decision trees, overfitting

Week 3:

Instance based learning, Feature reduction, Collaborative filtering based recommendation

Week 4:

Probability and Bayes learning

Week 5:

Logistic Regression, Support Vector Machine, Kernel function and Kernel SVM

Week 6:

Neural network: Perceptron, multilayer network, backpropagation, introduction to deep neural network

Week 7:

Computational learning theory, PAC learning model, Sample complexity, VC Dimension, Ensemble learning

Week 8:

Clustering: k-means, adaptive hierarchical clustering, Gaussian mixture model