deep learning education
Materials for the 'Learn PyTorch for Deep Learning: Zero to Mastery' course, including Jupyter notebooks and tutorials for learning deep learning from scratch using PyTorch.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose for TensorFlow-based deep learning tutorials; it's archived and stale, so only if you need TF examples.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Choose for a well-maintained, TensorFlow-based intro to deep learning from MIT.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Choose for a top-down deep learning course using fastai's high-level API instead of raw PyTorch.
The fastai book, published as Jupyter Notebooks
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Narrower deep NLP lectures from 2017; choose only for that specific topic.
Oxford Deep NLP 2017 course
Narrower: RL-only course; choose if you specifically need reinforcement learning.
A course in reinforcement learning in the wild
These projects were analysed and named pytorch-deep-learning among their alternatives. The relationship is not symmetric — how pytorch-deep-learning rates them is a separate judgement, made when pytorch-deep-learning is analysed in its own right.
calls pytorch-deep-learning “choose when you want an up-to-date English video-led PyTorch course instead of a Chinese handbook.”
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
calls pytorch-deep-learning “For a structured zero-to-mastery PyTorch course with video follow-along.”
A resource for learning about Machine learning & Deep Learning
calls pytorch-deep-learning “choose if you prefer a video course + notebooks over a formal textbook; it's PyTorch-specific and actively maintained.”
邱锡鹏《神经网络与深度学习》第二版与通识版：电子书、章节目录、学习资源与勘误。
calls pytorch-deep-learning “PyTorch course notebooks; choose if you want a video/course format with PyTorch instead of the MIT theory book.”
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
calls pytorch-deep-learning “Choose when you want a PyTorch-first video course with project notebooks rather than MIT's model-focused labs.”
Lab Materials for MIT 6.S191: Introduction to Deep Learning
calls pytorch-deep-learning “Choose if you specifically want deep-learning instruction with PyTorch and modern tooling rather than a broad ML theory course.”
Machine Learning Course, Sharif University of Technology
calls pytorch-deep-learning “choose it for an in-depth, video-based PyTorch deep learning course rather than a broad AI survey.”
12 Weeks, 24 Lessons, AI for All!
calls pytorch-deep-learning “choose to specialize in PyTorch deep learning rather than broad AI engineering.”
Learn it. Build it. Ship it for others.
calls pytorch-deep-learning “Choose for a modern PyTorch deep-learning-only course (Zero to Mastery) instead of broad ML.”
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
calls pytorch-deep-learning “Pick for a project-based PyTorch course, but it does not provide the comprehensive theoretical coverage of the seed.”
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
calls pytorch-deep-learning “Choose it for a hands-on PyTorch deep-learning course instead of a broad ML engineering pipeline.”
Learn ML engineering for free in 4 months! Register here 👇🏼
calls pytorch-deep-learning “When you want a popular, beginner-friendly PyTorch deep learning zero-to-mastery course that doesn't cover classical ML.”
AI实战-practicalAI 中文版