notebooks and pytorch-tutorial

These are complementary resources, with the notebooks from dataflowr serving as practical course material that could utilize the broader theoretical understanding and examples provided by yunjey/pytorch-tutorial.

notebooks
61
Established
pytorch-tutorial
51
Established
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 1,259
Forks: 331
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 32,219
Forks: 8,263
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
No Package No Dependents
Stale 6m No Package No Dependents

About notebooks

dataflowr/notebooks

code for deep learning courses

About pytorch-tutorial

yunjey/pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

Covers fundamental to advanced architectures—from linear regression and CNNs through ResNets and RNNs, to GANs and variational autoencoders—with minimal, self-contained implementations (typically under 30 lines each). Structured progressively across basics, intermediate, and advanced modules, each with runnable examples and TensorBoard integration for visualization. Designed as a bridge between PyTorch's official quickstart and production research code.

Related comparisons

notebooks and pytorch-deep-learning notebooks and pytorch-deep-learning

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