| Jan 22 | what machine learning is | introductions of [IML], [ESML], and [DM] | |
| Jan 24 | introduction to probability / calculus | appendix A of [IML], sect 2.3.1 of [ESML] | |
| Jan 29 | Bayesian decision theory & KNN classifier | chapter 3, (optional) 8.2.3 of [IML] | homework1 |
| Jan 31 | Naive Bayes Classifier | sect 9.3, 9.4, 9.5 of [CIML] | |
| Feb 05 | travel, problem-solving session | | |
| Feb 07 | linear classifier & optimization | chp 7 and sect 9.7 of [CIML] | |
| Feb 12 | linear classifier & optimization | sect 9.7 of [CIML] | |
| Feb 14 | Classification evaluation | chp 5.5-5.8 of [CIML] | homework 2 & project 1 |
| Feb 19 | President’s Day, no class | | |
| Feb 21 | Linear classifier | sect 7.7 of [CIML] | |
| Feb 22 | SVM | sect 7.7 of [CIML] | |
| Feb 26 | Tree classifiers | sect 1.3 of [CIML] sect 4.3 of [DM] | |
| Feb 28 | Ensumble methods | chp 13 of [CIML] | |
| Mar 05 | Diagnosing classifiers | sect 5.8, 5.9 of [CIML] | |
| Mar 07 | hypothesis testing revisit, PAC learning theory | chp 12.1-12.3 of [CIML] | homework 3 |
| Mar 12 | Homework 3 solutions & introduction of project 2 | | project 2 |
| Mar 14 | midterm | | summary of discussed topics |
| Mar 19 | Spring Recess, no class | | |
| Mar 21 | Spring Recess, no class | | |
| Mar 26 | Learning theory | chp 12.4-12.6 of [CIML] | homework 4 |
| Mar 28 | Multiclass classification | chp 6.2 of [CIML] | |
| Apr 02 | Kernel methods | chp 11 of [CIML] | |
| Apr 04 | Collaborative filtering | chp 9 of “Mining of Massive Datasets” [link] | project 3 |
| Apr 09 | Clustering | chp 15 of [CIML] | |
| Apr 11 | Summary of unsupervised learning & Generative model | sect 16.2, 16.3 of [CIML] | |
| Apr 16 | Patriots’ Day, no class | | |
| Apr 18 | Generative model | sect 16.2, 16.3 of [CIML] | homework 5 |
| Apr 23 | Neural network | chp 10 of [CIML] | |
| Apr 25 | Deep Neural Network | | |
| Apr 30 | Course review | | |