Course Schedule
Weekday Regular Schedule
Group | Type | Hours | Location |
---|---|---|---|
All | Lecture | Sunday 13:00-16:00 | Naftali 001 |
1 | Recitation | Wednesday 14:00-15:00 | Orenstein 103 |
2 | Recitation | Wednesday 15:00-16:00 | Orenstein 103 |
3 | Recitation | Wednesday 16:00-17:00 | Orenstein 111 |
Detailed Schedule
Lecture | Date | Topics | Lecturer | Slides | Scribes |
---|---|---|---|---|---|
1 | Oct. 30, 2016 | Introduction to the course and to machine learning. K-Nearest Neighbor algorithm | Yishay Mansour | lecture 1 | scribe 1 recitation 1 |
2 | Nov. 6, 2016 | PAC model and basic Generalization bounds | Yishay Mansour | lecture 2 | scribe 2 recitation 2 |
3 | Nov. 13, 2016 | Generalization bounds: VC dimension, Rademacher Complexity, Model Selection | Yishay Mansour | lecture 3 | scribe 3 recitation 3 |
4 | Nov. 20, 2016 | Perceptron algorithm and mistake bound | Yishay Mansour | lecture 4 | scribe 4 recitation 4 |
5 | Nov. 27, 2016 | Support Vector Machines (SVM) | Amir Globerson | lecture 5 | scribe 5 recitation 5 |
6 | Dec. 4, 2016 | Kernels | Amir Globerson | lecture 6 | scribe 6 recitation 6 |
7 | Dec. 11, 2016 | Stochastic Gradient Descent and Deep Learning | Amir Globerson | lecture 7 | scribe 7 recitation 7 |
8 | Dec. 18, 2016 | Decision Trees | Yishay Mansour | lecture 8 | scribe 8 recitation 8 |
Dec. 25, 2016 | SVD (Hanukkah) | recitation 9 | |||
9 | Jan. 1, 2017 | Boosting and ensemble methods | Yishay Mansour | lecture 9 | scribe 9 recitation 10 |
10 | Jan. 8, 2017 | Regression and PCA | Amir Globerson | lecture 10 | scribe 10 recitation 11 |
11 | Jan. 15, 2017 | Clustering and Generative Models | Amir Globerson | lecture 11 | (no scribe) recitation 12 |
12 | Jan. 22, 2017 | Gaussian mixture model (GMM) and Expectation Maximization (EM) | Amir Globerson | lecture 12 | scribe 12 recitation 13 (pdf) |
13 | Jan. 29, 2017 | Graph Based Methods and Summary | Amir Globerson | lecture 13 |
Previous years' scribes are available here.