deep learning education / book code notebooks
Jupyter notebooks containing the runnable code samples from the book 'Deep Learning with Python' by François Chollet.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
choose it for a broader, actively maintained ML/DL book with TF2/Keras notebooks.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
choose it for an actively maintained university deep learning course with PyTorch notebooks.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
choose it for a rigorous theoretical deep learning textbook in PDF rather than runnable code.
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
choose it for the fastai/PyTorch book style of learning deep learning, though the repo has not been updated in over 18 months.
The fastai book, published as Jupyter Notebooks
choose it for Nielsen's classic deep learning book code, though it is unmaintained.
Code samples for my book "Neural Networks and Deep Learning"
choose it if you need Raschka's 2nd-edition ML book code, though it is stale.
The "Python Machine Learning (2nd edition)" book code repository and info resource
choose it for the 3rd edition of Raschka's ML book code, though not recently updated.
The "Python Machine Learning (3rd edition)" book code repository
choose it for fast.ai's course notebooks, though they are several years outdated.
The 3rd edition of course.fast.ai
choose it for a comprehensive multi-framework deep learning textbook codebase, though not updated recently.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
choose it for a Chinese TF2-based deep learning book code repo, now stale.
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
choose it only for legacy TensorFlow 1 teaching examples, now archived.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
choose it for the Chinese edition of the D2L deep learning book code, though not recently pushed.
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
choose it for a broad machine learning notebook survey, though it is inactive and not deep-learning-focused.
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
choose it for the original edition of Raschka's ML book code, though the content is dated.
The "Python Machine Learning (1st edition)" book code repository and info resource
These projects were analysed and named deep-learning-with-python-notebooks among their alternatives. The relationship is not symmetric — how deep-learning-with-python-notebooks rates them is a separate judgement, made when deep-learning-with-python-notebooks is analysed in its own right.
calls deep-learning-with-python-notebooks “Companion code for Keras book; choose to follow that book's examples.”
Code samples for my book "Neural Networks and Deep Learning"
calls deep-learning-with-python-notebooks “English Keras-focused deep learning book with notebooks; choose if you prefer the Keras API and English content.”
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
calls deep-learning-with-python-notebooks “Choose when you already know classic ML and need a Keras/TensorFlow deep-learning-only companion.”
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
calls deep-learning-with-python-notebooks “when you want Keras-first code samples from Chollet's book instead of broad video-course notes.”
✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
calls deep-learning-with-python-notebooks “When you want a deep-learning-focused companion (Keras).”
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
calls deep-learning-with-python-notebooks “When you want Keras/deep-learning-only book code instead of broad classical ML coverage.”
The "Python Machine Learning (2nd edition)" book code repository and info resource