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21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
The fastai book, published as Jupyter Notebooks
Learn OpenCV : C++ and Python Examples
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
wtfpython的中文翻译/持续🚧.../ 能力有限，欢迎帮我改进翻译
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
this repository accompanies the book "Grokking Deep Learning"
Python training for business analysts and traders
Understanding Deep Learning - Simon J.D. Prince
Flax is a neural network library for JAX that is designed for flexibility.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
Segment Anything in Medical Images
Repository for benchmarking graph neural networks
Code Repository for The Kaggle Book, Published by Packt Publishing
Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。
A fast gigapixel processing system
Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L
Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻🦸🏽
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
書籍「つくりながら学ぶ! PyTorchによる発展ディープラーニング」の実装コードを配置したリポジトリです
Awesome Machine Unlearning (A Survey of Machine Unlearning)
Graph Machine Learning course, Xavier Bresson, 2023
An Intuitive Tutorial to Gaussian Processes Regression