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UCSD ECE176: Introduction to Deep Learning & Applications (Winter)
| Date |
Lecture |
Materials |
Assignments |
| Jan 6 |
Introduction |
Lecture 1 |
|
| Jan 8 |
Nearest Neighbor and Linear Classifiers |
|
Assignment 1 |
| Jan 9 |
Jupyter Notebook Tutorial |
|
|
| Jan 13 |
Linear Classifier and Optimization |
|
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| Jan 15 |
MLP and Back-Propagation |
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Assignment 2 |
| Jan 16 |
Assignment 1 Due |
| Jan 20 |
Intro to CNN and Back-Propagation with CNN |
|
|
| Jan 22 |
Different Elements in Training CNNs 1 |
|
Assignment 3 |
| Jan 23 |
Assignment 2 Due |
| Jan 27 |
Different Elements in Training CNNs 2 |
|
|
| Jan 29 |
Tutorial on Pytorch |
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Assignment 4 |
| Jan 30 |
Assignment 3 Due |
| Feb 3 |
Deep Network Architectures |
|
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| Feb 5 |
Image Segmentation |
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| Feb 6 |
Final Project Proposal Due |
| Feb 10 |
Visualizing Deep Networks |
|
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| Feb 12 |
Object Detection 1: Box |
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Assignment 5 |
| Feb 13 |
Assignment 4 Due |
| Feb 17 |
Object Detection 2: Mask and Pose |
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| Feb 19 |
Recurrent Neural Networks |
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| Feb 24 |
Video Understanding |
|
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| Feb 26 |
Video Prediction |
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Assignment 6 |
| Feb 27 |
Assignment 5 Due |
| Mar 3 |
Vision Transformer |
|
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| Mar 5 |
Generative Adversarial Networks |
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| Mar 10 |
Conditional Generative Adversarial Networks |
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| Mar 12 |
Guest Lecture |
|
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| Mar 15 |
Assignment 6 Due, Final Project Due |
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