| Sep 5 | What machine learning is (slides) | Section 1.1 - 1.3 of [CIML] | |
| Sep 10 | Introduction to calculus and linear algebra (notes) | Math for Machine Learning | |
| Sep 12 | Introduction to probability (slides) | Chapter 2 of [MLPP] (in piazza resource) | |
| Sep 17 | Bayesian decision theory (slides) | Section 1.4 - 1.5, 2.1 - 2.5 of [CIML] | Homework 1 |
| Sep 19 | Bayesian decision theory (continue) | | |
| Sep 24 | Tree classifiers (slides) | Section 1.3 of [CIML], also Ch3 of [ML] | |
| Sep 26 | K-Nearest Neighbor Classifier (slides) | Chapter 3 of [CIML] | |
| Oct 1 | Linear Classifier & Optimization (slides) | Section 7.1-7.6 of [CIML] | Homework 2 |
| Oct 3 | Linear Classifier & Optimization (cont.) | | Project 1 |
| Oct 9 | Classifier evaluation (slides) | Section 5.5-5.7 of [CIML] | |
| Oct 10 | Support Vector Machines (slides) | Chapter 7.7 of [CIML] | |
| Oct 15 | Diagnosing classifiers (slides) | Chapter 5.8, 5.9 of [CIML] | |
| Oct 17 | Bagging and Random Forest (slides) | Chapter 13 of [CIML], also Chapter 15 of [ESL] | |
| Oct 22 | Boosting (slides in the previous deck) | Chapter 13 of [CIML], also Chapter 10 of [ESL] | Homework 3 |
| Oct 24 | Probabilistic Models (slides) | Chapter 9 of [CIML] | |
| Oct 29 | Midterm preparation, project1 & classifier summary | | |
| Oct 31 | midterm | Summary of discussed topics | |
| Nov 5 | Feature Preparation (slides) | Section 5.1-5.4 of [CIML] | Homework 4, Project 2 |
| Nov 7 | Multiclass classification (slides) | Section 6.2 of [CIML] | |
| Nov 12 | holiday, no class | | |
| Nov 14 | Collaborative filtering (slides) | Chapter 9 of “Mining of Massive Datasets” [link] | |
| Nov 19 | Clustering (slides) | Chapter 15 of [CIML] | |
| Nov 21 | holiday, no class | | Project 3 |
| Nov 26 | PAC learning theory (slides) | Chapter 12.1-12.6 of [CIML] | Homework 5 |
| Nov 28 | Generative model (slides) | Section 16.2, 16.3 of [CIML] | |
| Dec 3 | Neural network (slides, not used in class) | Chapter 10 of [CIML] | |
| Dec 5 | Deep Neural Network (slides) | | |
| Dec 10 | Course Summary (slides) | | |