jeffheaton/app_deep_learning
T81-558: PyTorch - Applications of Deep Neural Networks @Washington University in St. Louis
This project contains educational materials for a deep learning course that teaches how to build advanced AI models. It takes various forms of data like images, text, audio, and structured tables as input to produce classifications, predictions, or generated content. The primary users are individuals, such as data scientists, machine learning engineers, or researchers, looking to apply deep learning techniques to real-world challenges.
485 stars.
Use this if you want to learn how to implement and apply deep neural networks for tasks like computer vision, natural language processing, time series analysis, or data generation using Python and PyTorch.
Not ideal if you are looking for a plug-and-play software solution or do not have any programming experience.
Stars
485
Forks
184
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jan 20, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jeffheaton/app_deep_learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
dataflowr/notebooks
code for deep learning courses
dvgodoy/PyTorchStepByStep
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
xl0/lovely-tensors
Tensors, for human consumption
rentruewang/koila
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.
mrdbourke/pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.