hse-aml/intro-to-dl
Resources for "Introduction to Deep Learning" course.
This provides ready-to-use learning materials, including Jupyter notebooks, for an "Introduction to Deep Learning" course. It offers a structured way to practice and experiment with deep learning concepts, with pre-configured environments for Google Colab, Docker, or Anaconda. It's designed for students and self-learners taking an introductory deep learning course.
755 stars. No commits in the last 6 months.
Use this if you are taking an 'Introduction to Deep Learning' course and need a reliable, pre-configured environment to run assignments and experiments with deep learning models, potentially leveraging free GPU resources.
Not ideal if you are looking for a general-purpose deep learning development library or a tool for deploying deep learning models in production.
Stars
755
Forks
710
Language
Jupyter Notebook
License
—
Category
Last pushed
Sep 09, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/hse-aml/intro-to-dl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PaddlePaddle/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice...
fastai/fastai
The fastai deep learning library
openvinotoolkit/openvino_notebooks
📚 Jupyter notebook tutorials for OpenVINO™
PaddlePaddle/docs
Documentations for PaddlePaddle
msuzen/bristol
Parallel random matrix tools and complexity for deep learning