Paperspace/PyTorch-101-Tutorial-Series
PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.
This series of Jupyter notebooks and accompanying blog posts teaches you how to build deep learning models using PyTorch. Starting with fundamental concepts like computation graphs, it guides you through constructing neural networks, managing memory, and using advanced features. It's designed for data scientists, machine learning engineers, and researchers looking to learn or deepen their understanding of PyTorch.
266 stars. No commits in the last 6 months.
Use this if you are a developer looking for a structured, hands-on introduction to building and understanding deep learning models with PyTorch.
Not ideal if you are looking for a pre-built solution for a specific machine learning task rather than a learning resource for PyTorch.
Stars
266
Forks
57
Language
Jupyter Notebook
License
—
Category
Last pushed
Aug 19, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Paperspace/PyTorch-101-Tutorial-Series"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mrdbourke/pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
xl0/lovely-tensors
Tensors, for human consumption
stared/livelossplot
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
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"