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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

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