Machine Learning - Coursera University of Washington Course 1:Regression Week 1: Introduction & Simple Linear Regression Week 2: Multiple Regression Week 3: Assessing Performance Week 4: Ridge Regression Week 5: Feature Selection & Lasso Week 6: Nearest Neighbors & Kernel Regression Course 2:Classification Week 1: Linear Classifiers & Logistic Regression Week 2: Overfitting & Regularization in Logistic Regression Week 3: Decision Trees Week 4: Preventing Overfitting in Decision Trees & Handling Missing Data Week 5: Boosting (Adaboost) Week 6: Precision-Recall Week 7: Scaling to Huge Datasets & Online Learning Course 3:Clustering & Retrieval Week 1: Introduction Week 2: Nearest Neighbor Search (Brute-Force, KD-tree and LSH) Week 3: Clustering with k-means Week 4: Mixture Models (GMM and EM algorithm) Week 5: Mixed Membership Modeling via Latent Dirichlet Allocation Week 6: Hierarchical Clustering