A tentative plan for the schedule (topics, deadlines, etc.) is available here.
Schedule (subject to change as the term progresses)
- Resource
- PyTorch Tutorial (w/ links to Colab notebook)
- Jan 6
- Course Overview
- Eisenstein 1
- Jan 8
- Machine Learning Review - linear classification (notes)
- Eisenstein 1
- Jan 9
- Problem Set 0 due
- Jan 13
- Machine Learning Review - logistic regression, perceptron, SVM (notes)
- Eisenstein 2.0-2.5, 4.1, 4.3-4.5, J+M 5
- Jan 15
- Machine Learning Review - mutliclass classification
- Eisenstein 2.0-2.5, 4.1, 4.3-4.5, J+M 5
- Jan 17
- Project 0 due
- Jan 20
- no class - holiday
- Jan 22
- Neural Networks - Feedforward, optimization
- Eisenstein 2.6, 3.1-3.3, J+M 7, Goldberg 1-4
- Jan 28
- Problem Set 1 due