Subject to change.
| Date | Topics | Readings | |
|---|---|---|---|
| Th Jan 26 | Welcome to Machine Learning | ||
| Tu Jan 31 | Decision Trees | CIML 1 + Syllabus | |
| Th Feb 2 | Limits of learning; Overfitting/Underfitting | CIML 2 | |
| Tu Feb 7 | Geometry and nearest neighbors | CIML 3-3.3 | |
| Th Feb 9 | K-means clustering | CIML 3.4-3.5 | |
| Tu Feb 14 | Perceptron I | CIML 4-4.5 | |
| Th Feb 16 | Perceptron II | CIML 4.5-4.7 | |
| Tu Feb 21 | Practical Issues | CIML 5-5.5 | |
| Th Feb 23 | Learning from Imbalanced Data | CIML 6.1 | |
| Tu Feb 28 | Beyond Binary Classification | CIML 6.2-6.3 | |
| Th Mar 2 | Ranking reductions/Catch-up/Practice Problems | ||
| Tu Mar 7 | MIDTERM | ||
| Th Mar 9 | Linear Classifiers and Gradient Descent | CIML 7-7.4 | |
| Tu Mar 14 | Snow day | ||
| Th Mar 16 | Sub-gradient descent | CIML 7.5-7.7 | |
| Spring Break! | |||
| Tu Mar 28 | Probabilistic Models I | CIML 9-9.5 | |
| Th Mar 30 | Probabilistic Models II | CIML 9.6-9.7 | |
| Tu Apr 4 | Neural Networks I | CIML 10-10.3 | |
| Th Apr 6 | Neural Networks II | CIML 10.4-10.6 | |
| Tu Apr 11 | PCA | CIML 15-15.2 | |
| Th Apr 13 | Lab: Practice Problems | ||
| Tu Apr 18 | Kernels | CIML 11-11.3 | |
| Th Apr 20 | Support Vector Machines I | CIML 11.4-11.6 | |
| Tu Apr 25 | Support Vector Machines II | CIML 11.4-11.6 | |
| Th Apr 27 | Bias and Fairness | CIML 8 | |
| Tu May 2 | Deep Learning I | ||
| Th May 4 | Deep Learning II (see slides from May 2) | ||
| Tu May 9 | Review and Perspectives | ||
| Th May 11 |