yunjey/pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

51
/ 100
Established

This project provides practical code examples for deep learning models, helping you understand how to implement various neural networks. You'll start with basic concepts like linear and logistic regression, progressing to more complex models such as Convolutional Neural Networks and Generative Adversarial Networks. It's designed for deep learning researchers and practitioners who want to learn how to build these models using PyTorch.

32,219 stars. No commits in the last 6 months.

Use this if you are a deep learning researcher looking for concise, runnable code examples to learn PyTorch by implementing various neural network architectures.

Not ideal if you are looking for a conceptual introduction to deep learning theory or a beginner's guide to Python programming.

deep-learning-research neural-networks machine-learning-implementation computer-vision natural-language-processing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

How are scores calculated?

Stars

32,219

Forks

8,263

Language

Python

License

MIT

Last pushed

Aug 15, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yunjey/pytorch-tutorial"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.