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University of Michigan
Lecture 1: Introduction to Deep Learning for Computer Vision.Lecture 2: Image Classification.Lecture 3: Linear Classifiers.Lecture 4: Optimization.Lecture 5: Neural Networks.Lecture 6: Backpropagation.Lecture 7: Convolutional Networks.Lecture 8: CNN Architectures.Lecture 9: Hardware and Software.Lecture 10: Training Neural Networks I.Lecture 11: Training Neural Networks II.Lecture 12: Recurrent Networks.Lecture 13: Attention.Lecture 14: Visualizing and Understanding.Lecture 15: Object Detection.Lecture 16: Detection and Segmentation.Lecture 17: 3D Vision.Lecture 18: Videos.Lecture 19: Generative Models I.Lecture 20: Generative Models II.Lecture 21: Reinforcement Learning.Lecture 22: Conclusion.
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