CMPE462 - Machine Learning
Spring 2018
Instructor: Ali Taylan Cemgil
(Volunteer) Student TA: Riza Ozcelik
Bogazici University, Department of Computer Engineering, Istanbul, Turkey
Announcements
Follow cmpe462 on twitter
Github site for project submissions
Jupyter Notebooks (in preperation)
Slides
Timetable
7-8 Feb | Introduction, Linear Algebra and Probability review | |
14-15 Feb | Supervised Learning, Linear Regression | |
21-22 Feb | Classification, Naive Bayes, k-nearest neighbors, decision trees, model evaluation | |
28 Feb 1 Mar | Classification, Logistic Regression | |
7-8 Mar | Optimization, Gradient Descent, Newton's method, Momentum | |
14-15 Mar | Regularization, Feature selection, Support vector machines | |
21-22 Mar | Artificial Neural Networks (ANNs) | |
28-29 Mar | Deep Learning Frameworks, PyTorch, Automatic Differentiation | |
4-5 Apr | Unsupervised Learning, k-means clustering, spectral clustering | |
11-12 Apr | Dimensionality reduction, Singular Value Decomposition, Principal Component Analysis | |
Spring Break | | |
25-26 Apr | Matrix Decompositions, Nonnegative Matrix Factorization, Recommendation systems | |
2-3 May | Exam | |
9-10 May | Review and what next? | |
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Reference Textbooks
Administrative
Grading
Total Credits
3
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