aMLT | Notes

Karthik Thiagarajan

The content presented here has been drawn from the lectures recorded by professor Arun Rajkumar for the Machine Learning Techniques course and the notes that he generated while recording them. This content can be assumed to a loose adaption of the professor's lectures in written form. If any errors are found in this document, please drop a mail to karthik@study.iitm.ac.in.

Week	Content
Notation
Symbol Soup	A formula sheet for the course (under construction)
Week-1	PCA
Week-2	Kernel PCA
Week-3	K-Means
Week-4	Estimation, MLE, Bayesian, EM algorithm
Week-5	Linear regression, Kernel regression
Week-6	Regularization, Ridge and Lasso regression
Week-7	Classification, KNN, Decision Trees
Week-8	Discriminative and generative models, Naive Bayes
Week-9	Perceptron, Logistic Regression
Week-10	Hard-Margin SVM
Week-11	Soft-Margin SVM, Bagging, Boosting, AdaBoost
Week-12	Loss functions for classification, Neural networks