Course Schedule

Weekday Regular Schedule

Group Type Hours Location
All Lecture Sunday 13-15 Holcblat 7
1 Recitation Sunday 15-16 Orenstein 111
2 Recitation Sunday 16-17 Dan David 203

*New* Proofreading for Bonus Program

The scribes of the course have been carefully proofread, still, there are always typos left. Please use the form
to report typos. Each student can claim up to 5 bonus points. Each NEWLY DISCOVERED math typo is worth 1pt, each NEW English typo is worth 0.5pt.
Points will be awarded after verification by one of the lecturers or the TA.
You can also point to typos in the slides. 0.5pt each (English or Math).

Detailed Schedule

Lecture Date Lecture topics lecturer Lecture slides Scribes
1 Oct. 13, 2013 Introduction to the course and to machine learning. K-Nearest Neighbor algorithms, and k-means algorithms Lior Wolf Lecture
Recitation Figures
2 Oct. 20, 2013 Bayesian Inference Eran Halperin BayesianInferenceLectures1-2.pdf. Lecture
3 Oct. 27, 2013 Gaussian Mixture Model (GMM) and Expectation Maximization (EM) Eran Halprin Lecture
4 Nov. 3, 2013 Probably Approximately Correct (PAC) model.
including generalization bounds and model selection.
Yishay Mansour Lecure 4 PAC Lecture
5 Nov. 10, 2013 Basic hyperplane algorithms: Perceptron and Winnow. Yishay Mansour Online Learning Lecture
6 Nov. 17, 2013 Support Vector Machines (SVM) Lior Wolf SVM Lecture
7 Nov. 24, 2013 Kernels Lior Wolf Kernels (we only got as far as Kernel SVD) Lecture
8 Dec. 8, 2013 Boosting weak learners to strong learners: AdaBoost Yishay Mansour Boosting Lecture
9 Dec. 15, 2013 Regression problems Eran Halperin Regression Lecture
10 Dec. 22, 2013 Principle Component Analysis (PCA) Eran Halperin PCA Lecture
11 Dec. 29, 2013 Finish PCA start
Decision trees
Yishay Mansour Decision Trees Lecture
12 Jan. 5, 2014 Decision trees pruning and random forest Yishay Mansour Decision Trees - part 2 Lecture
13 Jan. 12, 2014 Applications Lior Wolf Applications
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