Machine learning theory: Slides
Sharif university of technology - Mathematics and Computer science department
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The slides for each session are created by Dr. Seyyedsalehi, the course instructor, and will be available on both Quera and here after every lecture. |
Spring 2024
- 01-Introduction
- 02-Linear Regression
- 03-Linear classifiers
- 04-Probabilistic Perspective of Learning
- 05-Probabilistic classifiers P1
- 06-Probabilistic classifiers P2
- 07 and 08-Feature maps and kernels
- 09 to 11-Generalization
- 12-Computational learning theory
- 13 and 14-SVM
- 15-Neural networks
- 16-Decision Tree
- 17 and 18-Nonparametric learning
- 19-Endemble learning
- 20-Dimensionality reduction
- 21-Clustering
- 22-EM and GMM.
- 23 and 24-RL
- 25 and 26-Interpretability