arthurdouillard/deepcourse
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki
This course helps you master Deep Learning for Computer Vision. It provides clear theoretical explanations, practical PyTorch coding examples, and uses Anki for spaced repetition to help you retain information. It's designed for engineering students or anyone looking to build a strong foundation in computer vision.
149 stars. No commits in the last 6 months.
Use this if you are an engineering student or a professional who wants to systematically learn the fundamentals and state-of-the-art techniques in deep learning for computer vision.
Not ideal if you are looking for a quick reference guide or an advanced research resource rather than a structured learning path.
Stars
149
Forks
18
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Dec 07, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/arthurdouillard/deepcourse"
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"