PyQdeckBEU PYQ Archive Subjects Syllabus Blog

Machine Learning

105602

6 modules · 39 topics · 39 with study notes

Module 1Introduction7 topics

Basic Definitions Notes
Linear Algebra Notes
Statistical Learning Theory Notes
Types of Learning Notes
Hypothesis Space and Inductive Bias Notes
Evaluation and Cross Validation Notes
Optimization Notes

Module 2Statistical Decision Theory and Bayesian Learning7 topics

Statistical Decision Theory Notes
Bayesian Learning — ML, MAP, Bayes Estimates, Conjugate Priors Notes
Linear Regression Notes
Ridge Regression Notes
Lasso Notes
Principal Component Analysis Notes
Partial Least Squares Notes

Module 3Linear Classification and Advanced Methods10 topics

Linear Classification Notes
Logistic Regression Notes
Linear Discriminant Analysis Notes
Quadratic Discriminant Analysis Notes
Perceptron Notes
Support Vector Machines + Kernels Notes
Artificial Neural Networks + Back Propagation Notes
Decision Trees Notes
Bayes Optimal Classifier Notes
Naive Bayes Notes

Module 4Hypothesis Testing and Ensemble Methods5 topics

Hypothesis Testing Notes
Ensemble Methods Notes
Bagging Notes
Adaboost Notes
Gradient Boosting Notes

Module 5Clustering5 topics

Clustering Notes
K-means Notes
K-medoids Notes
Density-based Hierarchical Notes
Spectral Notes

Module 6Advanced Topics5 topics

Expectation Maximization Notes
GMMs Notes
Learning Theory Notes
Introduction to Reinforcement Learning Notes
Bayesian Networks Notes

Theory