TomasBeuzen/deep-learning-with-pytorch
Content from the University of British Columbia's Master of Data Science course DSCI 572.
This content introduces you to deep learning concepts and their practical application using PyTorch. It guides you through building neural networks for tasks like image classification and generating synthetic images, using real data as input to produce trained models and insights. This resource is for students, researchers, or data science practitioners looking to understand and implement deep learning.
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Use this if you want to learn the fundamentals of deep learning, including neural networks, convolutional neural networks, and generative adversarial networks, using the PyTorch framework.
Not ideal if you are looking for an advanced deep learning research reference or a platform to deploy production-ready models without prior learning.
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Jupyter Notebook
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CC0-1.0
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Jun 09, 2021
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