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Computer Vision with PyTorch


Computer vision algorithms, which process video and image data, have many applications. The development of convolutional neural networks, alongside hardware improvements, have led to a proliferation of highly accurate computer vision models. In this tutorial, you will learn how to build new, and use existing, computer vision models using PyTorch.

This tutorial is a practical, hands-on, introduction to computer vision with PyTorch.

In this tutorial, you will learn about:
- An overview of deep learning for computer vision
- How to implement neural networks in PyTorch
You will gain hands-on experience with important computer vision tasks:
- Image classification
- Object detection
- Semantic segmentation
- Generative models

Tutorial materials are available on GitHub in Jupyter notebook format.

Laptops are encouraged, but not required.


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