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CSE 4095/5095
Deep Learning
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(Tentative schedule for the course and deviations may be necessary as the course progresses.)
| Date |
Topic |
Notes |
Reading (Textbook or Other Materials) |
| Aug. 25 |
Introduction |
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Chapter 1, 2, 3, Nature review on DL, Basic calculus refresher |
| Aug. 27, 29 |
Machine Learning Basics |
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Chapter 4, 5, Machine learning math essentials |
| Sept. 3 |
Shallow Classifiers |
Project Details |
Chapter 4, 5 |
| Sept. 5 |
Loss Functions |
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Chapter 4, 5 |
| Sept. 8, 12 |
Optimization, SGD |
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Chapter 4, 5 |
| Sept. 15 |
Backpropagation |
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Chapter 4, 5 |
| Sept. 17, 19 |
Intro to Neural Networks |
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| Sept. 22 |
Intro to Convolutional Neural Networks, Convolution |
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AlexNet |
| Sept. 24, 26 |
Pooling, Demo, BP example |
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All Convolutional Net |
| Sept. 29 |
Training Neural Networks |
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| Oct. 1 |
Training Neural Networks II, Batch Normalization |
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Batch Normalization |
| Oct. 6 |
Second-order Optimization |
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Chapter 8 |
| Oct. 8 |
Regularization, Transfer Learning |
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Dropout, Blackout, DeCAF |
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