|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Tensorflow||172,434||327||77||11 hours ago||46||October 23, 2019||2,292||apache-2.0||C++|
|An Open Source Machine Learning Framework for Everyone|
|Transformers||87,738||64||911||10 hours ago||91||June 21, 2022||617||apache-2.0||Python|
|🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.|
|Keras||57,713||330||2 days ago||68||May 13, 2022||372||apache-2.0||Python|
|Deep Learning for humans|
|Tensorflow Examples||42,312||5 months ago||218||other||Jupyter Notebook|
|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|
|Photoprism||25,246||4||2 days ago||151||April 25, 2021||407||other||Go|
|AI-Powered Photos App for the Decentralized Web 🌈💎✨|
|Handson Ml||24,975||a day ago||136||apache-2.0||Jupyter Notebook|
|⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.|
|Ray||24,738||80||199||10 hours ago||76||June 09, 2022||2,900||apache-2.0||Python|
|Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.|
|Handson Ml2||24,269||21 days ago||193||apache-2.0||Jupyter Notebook|
|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.|
|Data Science Ipython Notebooks||23,924||5 months ago||26||other||Python|
|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.|
|Visualizer for neural network, deep learning, and machine learning models|
This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code and solutions to the exercises in the second edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow:
Note: If you are looking for the first edition notebooks, check out ageron/handson-ml. For the third edition, check out ageron/handson-ml3.
Use any of the following services (I recommended Colab or Kaggle, since they offer free GPUs and TPUs).
WARNING: Please be aware that these services provide temporary environments: anything you do will be deleted after a while, so make sure you download any data you care about.
github.com's notebook viewer also works but it's not ideal: it's slower, the math equations are not always displayed correctly, and large notebooks often fail to open.
Read the Docker instructions.
Start by installing Anaconda (or Miniconda), git, and if you have a TensorFlow-compatible GPU, install the GPU driver, as well as the appropriate version of CUDA and cuDNN (see TensorFlow's documentation for more details).
Next, clone this project by opening a terminal and typing the following commands (do not type the first
$ signs on each line, they just indicate that these are terminal commands):
$ git clone https://github.com/ageron/handson-ml2.git $ cd handson-ml2
Next, run the following commands:
$ conda env create -f environment.yml $ conda activate tf2 $ python -m ipykernel install --user --name=python3
Finally, start Jupyter:
$ jupyter notebook
If you need further instructions, read the detailed installation instructions.
Which Python version should I use?
I recommend Python 3.8. If you follow the installation instructions above, that's the version you will get. Most code will work with other versions of Python 3, but some libraries do not support Python 3.9 or 3.10 yet, which is why I recommend Python 3.8.
I'm getting an error when I call
Make sure you call
fetch_housing_data() before you call
load_housing_data(). If you're getting an HTTP error, make sure you're running the exact same code as in the notebook (copy/paste it if needed). If the problem persists, please check your network configuration.
I'm getting an SSL error on MacOSX
You probably need to install the SSL certificates (see this StackOverflow question). If you downloaded Python from the official website, then run
/Applications/Python\ 3.8/Install\ Certificates.command in a terminal (change
3.8 to whatever version you installed). If you installed Python using MacPorts, run
sudo port install curl-ca-bundle in a terminal.
I've installed this project locally. How do I update it to the latest version?
How do I update my Python libraries to the latest versions, when using Anaconda?
I would like to thank everyone who contributed to this project, either by providing useful feedback, filing issues or submitting Pull Requests. Special thanks go to Haesun Park and Ian Beauregard who reviewed every notebook and submitted many PRs, including help on some of the exercise solutions. Thanks as well to Steven Bunkley and Ziembla who created the
docker directory, and to github user SuperYorio who helped on some exercise solutions.