machine learning education
Code and Jupyter notebooks for the 'Python Machine Learning, 2nd Edition' book, teaching machine learning and deep learning with scikit-learn and TensorFlow.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
When you want the actively maintained code for Geron's book with scikit-learn and TensorFlow 2.
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.
When you want a free open online course with assignments and a community rather than a book's code.
Open Machine Learning Course
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
When you want Keras/deep-learning-only book code instead of broad classical ML coverage.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
When you are following the deprecated first edition and need the original TensorFlow-1 code.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
When you want self-contained historical blog notebooks on ML/statistics instead of a structured book.
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
When you prefer learning algorithms through plain-Python from-scratch implementations.
Plain python implementations of basic machine learning algorithms
When you want MIT's deep-learning lab exercises, but note it covers only deep learning.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
When you want university Keras course materials focused on applied deep learning.
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
When you need a PyTorch-focused deep learning tutorial in Chinese rather than sklearn/TensorFlow.
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
When you want a theory-heavy Chinese textbook on neural networks/deep learning.
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。
These projects were analysed and named python-machine-learning-book-2nd-edition among their alternatives. The relationship is not symmetric — how python-machine-learning-book-2nd-edition rates them is a separate judgement, made when python-machine-learning-book-2nd-edition is analysed in its own right.
calls python-machine-learning-book-2nd-edition “choose it if you need Raschka's 2nd-edition ML book code, though it is stale.”
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
calls python-machine-learning-book-2nd-edition “When you want the older 2nd edition of the rasbt book.”
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.