https://github.com/arnas/awesome-pytorch-scholarship
A list of awesome PyTorch scholarship articles, guides, blogs, courses and other resources.
https://github.com/arnas/awesome-pytorch-scholarship
pytorch scholarship udacity
Last synced: 4 months ago
JSON representation
A list of awesome PyTorch scholarship articles, guides, blogs, courses and other resources.
- Host: GitHub
- URL: https://github.com/arnas/awesome-pytorch-scholarship
- Owner: arnas
- License: mit
- Archived: true
- Created: 2018-11-09T22:54:47.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2018-11-24T05:11:33.000Z (almost 7 years ago)
- Last Synced: 2024-05-19T19:52:21.458Z (over 1 year ago)
- Topics: pytorch, scholarship, udacity
- Size: 74.2 KB
- Stars: 310
- Watchers: 28
- Forks: 69
- Open Issues: 1
-
Metadata Files:
- Readme: README.MD
- License: LICENSE
Awesome Lists containing this project
- Awesome-pytorch-list-CNVersion - awesome-pytorch-scholarship
- Awesome-pytorch-list - awesome-pytorch-scholarship
README
# Awesome PyTorch Scholarship Resources
[](https://github.com/sindresorhus/awesome)
A collection of awesome PyTorch and Python learning resources.
Contributions are always welcome!
## Course Information
## AMA's
- [Pytorch AMA 11.09.2018](https://docs.google.com/document/d/19ELb_KZI4eIdT6Xj0O9A6xkQfd6kRFwtQ-9xtAGclqA/edit#heading=h.2gazcsgmxkub)
- (Alternate categorized version) [Pytorch AMA 11.09.2018](https://docs.google.com/document/d/1tvq1fq1BoeJ4reKf_WfFhcXhY3sfOazwKoZC6vq3gjk/edit)
- [AMA Session Wednesday, November 14th @ 4PM PST](https://slack-files.com/files-pri-safe/TDBKE3X9D-FE45NN5BL/pytorch_facebook_scholarship_ama_181114.pdf?c=1542254974-3abc545b243d7de481d2fb193ebbaddfd99526cb)
- [AMA_Session Transcript,Thurs , 11/15/18](https://slack-files.com/files-pri-safe/TDBKE3X9D-FE58W5GP7/ama-4_transcribe_15.11.18.pdf?c=1542336165-fbe529cf9961b022229bae9f5ee7b722b00a87d3)
# Resources
- [Resources](#resources)
- [Documentation](#documentation)
- [Courses](#courses)
- [Articles](#articles)
- [Tutorials](#tutorials)
- [Jupyter Notebooks](#jupyter-notebooks)
- [Books](#books)
- [Training and tutorials](#training-and-tutorials)
- [Misc](#misc)
## Documentation
* [Pytorch Official Documentation](https://pytorch.org/docs/stable/index.html)
## Courses
Courses that can you take alongside PyTorch scholarship course both Python and Machine Learning
* [Coursera' Machine Learning Course by Stanford](https://www.coursera.org/learn/machine-learning)
* [Coursera' Deep learning Specialization taught by Andrew Ng](https://www.coursera.org/learn/machine-learning)
* [Linear Algebra refresher course from Udacity](https://eu.udacity.com/course/linear-algebra-refresher-course--ud953)
* [Introductory courses(few hours each) about Python, ML, Pandas Data Visualisation, SQL, R, Deep Learning, Embeddings, and ML Explainability](https://www.kaggle.com/learn/overview)
* [Linear algebra lectures from Gilbert Strang (very great lectures](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/)
* [Pytorch course - basics are very well explained such as tensors and common operations](http://deeplizard.com/learn/playlist/PLZbbT5o_s2xrfNyHZsM6ufI0iZENK9xgG)
* [A Practical Introduction to deep learning](https://www.datacamp.com/courses/deep-learning-in-python)
* [Intro To machine learning by MIT professors.](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/lecture-videos/lecture-11-introduction-to-machine-learning/)
* [Practical deep learning course. For later on in the challenge, when everyone is comfortable with PyTorch](https://course-v3.fast.ai/)
* [2-Day Python course for Python beginners](https://developers.google.com/edu/python/)
* [Linear algebra](https://eu.udacity.com/course/linear-algebra-refresher-course--ud953)
* [mlcourse.ai is an open Machine Learning course by OpenDataScience. The course is designed to perfectly balance theory and practice; therefore, each topic is followed by an assignment with a deadline in a week. ](https://mlcourse.ai/)
* [François Fleuret course on DL with Pytorch at EPFL](https://documents.epfl.ch/users/f/fl/fleuret/www/dlc/)
* [Free, interactive, intuitive Python tutorials](https://www.datacamp.com/courses/intro-to-python-for-data-science)
* [EDX - Deep Learning with Python and PyTorch](https://courses.edx.org/courses/course-v1:IBM+DL0110EN+3T2018/course/)
* [EDX - Introduction to Python: Fundamentals](https://courses.edx.org/courses/course-v1:Microsoft+DEV274x+3T2018/course/)
* [EDX - Introduction to Python: Absolute Beginner](https://courses.edx.org/courses/course-v1:Microsoft+DEV236x+3T2018/course/)
* [Udemy - Machine Learning MasterClass](https://www.udemy.com/machine-learning-masterclass/)
## Articles
Content published on the Web.
* [PyTorch 101 for Dummies](https://medium.com/@dassangeet768/pytorch-101-for-dummies-like-me-2adfe3af2e40)
* [Using PyTorch with GPU in Google Colab](https://jovianlin.io/pytorch-with-gpu-in-google-colab/)
* [The best resources for Deep Learning from beginner to advance](https://www.kaggle.com/getting-started/37999)
## Tutorials
Walkthroughs and tutorials that help you learn ML and PyTorch.
* [Chintala's 60 Minute PyTorch Blitz](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html)
* [Pytorch Official List of Tutorials](https://pytorch.org/tutorials/)
* [PyTorch tutorial for beginners](https://github.com/Lplenka/PyTorch-Tutorial)
* [Contains code based tutorial for Pytorch](https://github.com/AyushExel/DeepTorch)
* [Free Python coding games from beginners to advanced](https://checkio.org/)
* [An introduction to PyTorch Tensors](https://github.com/TheDataSpartan/PyTorch/blob/master/PyTorch%20Tensor%20Notebook.ipynb)
* [Deep Learning Tutorial - LISA lab, University of Montreal](http://deeplearning.net/tutorial/deeplearning.pdf )
* [Numpy Tutorial - Stanford CS231n](https://cs231n.github.io/python-numpy-tutorial)
* [Kaggle tutorial for deep learning beginners](https://kaggle.com/kanncaa1/deep-learning-tutorial-for-beginners)
## Jupyter Notebooks
* [From basics to building CNN in PyTorch ](https://github.com/Lplenka/PyTorch-Tutorial)
## Books
Books - free and commercial
* [Interactive textbook on Neural Network Fundamentals. Beginner resource](http://cs231n.stanford.edu/)
* [Deep Learning book from Ian Goodfellow and Yoshua Bengio and Aaron Courville](https://www.deeplearningbook.org/)
## Videos
An assortment of conference and training videos.
### Training and tutorials
* [3blue1brown's Channel (Intuitive refreshers in neural networks and linear Algebra))](https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw/playlists)
* [Siraj's Channel (Topics and courses in AI, machine learning, decentralized apps, etc.)](https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A/playlists)
* [But what is a Neural Network? | Deep learning, chapter 1](https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi)
* [How to Learn Deep Learning (when you’re not a computer science Ph.D.)](https://vimeo.com/214233053)
* [ML concepts in plain language.](https://www.youtube.com/user/joshstarmer)
* [Deep Learning with PyTorch](https://www.youtube.com/watch?v=v5cngxo4mIg&list=PLZbbT5o_s2xrfNyHZsM6ufI0iZENK9xgG)
* [Deep Learning with PyTorch](https://www.youtube.com/watch?v=v5cngxo4mIg&list=PLZbbT5o_s2xrfNyHZsM6ufI0iZENK9xgG)
* [Introduction to PyTorch. Uses regression, classification and image recognition for teaching concepts such CNNs, FCNs, AutoGrad etc](https://www.youtube.com/playlist?list=PLbMqOoYQ3Mxw1Sl5iAAV4SJmvnAGAhFvK)
* [Intro to Neural Networks](https://www.youtube.com/watch?v=aircAruvnKk)
* [Deep Neural Networks with PyTorch](https://www.youtube.com/watch?v=_H3aw6wkCv0)
## Blogs
* [Neural Network for beginners blog](https://blog.statsbot.co/neural-networks-for-beginners-d99f2235efca)
* [Tutorial to take you from beginner to expert in Machine Learning](https://machinelearningmastery.com)
* [Computer Vision for Python](https://www.pyimagesearch.com)
## Misc
* [Chrome extension for speeding up youtube video playback speed](https://chrome.google.com/webstore/detail/youtube-playback-speed-co/hdannnflhlmdablckfkjpleikpphncik)