| 1 |
Introduction |
Lecture 1 |
Video 1 |
| 2 |
SVD and Image Compression |
Lecture 2 |
Video 2 |
| 3 |
SVD, Eigen Faces and Convolutions |
Lecture 3 |
Video 3 |
| 4 |
kMeans, kMeans++, tSNE |
Lecture 4 |
Video 4 |
| 5 |
Computational Complexity and Total Variation |
Lecture 5a Lecture 5b |
Video 5 |
| 6 |
Binary Classification |
Lecture 6 |
Video 6 |
| 7 |
Classification Metrics and Overfitting |
Lecture 7 |
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| 8 |
Introduction to Deep Learning |
Lecture 8 |
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| 9 |
Backprop, SGD and Overfitting |
Lecture 9 |
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| 10 |
Convolutional Neural Networks |
Lecture 10 |
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| 11 |
CNN Architectures |
Lecture 11 |
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| 12 |
ResNet |
Lecture 12 |
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| 13 |
Transfer Learning |
Lecture 13 |
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Lecture 13 Notebook |
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| 14 |
Object Detection |
Lecture 14 |
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| 15 |
YOLO for Object Detection |
Lecture 15 |
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| 16 |
Image Captioning Models |
Lecture 16 |
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| 17 |
Image Captioning and StyleNet |
Lecture 17 |
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| 18 |
Generative AI: GPT-3 and ChatGPT |
Lecture 18 |
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