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University of Michigan

Deep Learning for Computer Vision

University of Michigan via YouTube

Syllabus

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.

Taught by

Michigan Online

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