handson-ml2 README

The project's README from github.com/ageron/handson-ml2. As one markdown file: README.md.

Machine Learning Notebooks

⚠ THIS EDITION IS NOW OUTDATED. THE THIRD EDITION OF MY BOOK IS NOW AVAILABLE, AS WELL A PYTORCH VERSION AND MANY TRANSLATIONS.

This project is for the second edition, which is now outdated (it came out in 2019).

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.

Quick Start

Want to play with these notebooks online without having to install anything?

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.

  • Open In Colab

  • Open in Kaggle

  • Launch binder

  • Launch in Deepnote

Just want to quickly look at some notebooks, without executing any code?

  • Render nbviewer

  • 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.

Want to run this project using a Docker image?

Read the Docker instructions.

Want to install this project on your own machine?

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.

FAQ

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 load_housing_data()

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?

See INSTALL.md

How do I update my Python libraries to the latest versions, when using Anaconda?

See INSTALL.md

Contributors

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.

handson-ml2 (ageron/handson-ml2)

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29.9K ·GitHub
Handson-ml2
这是什么？这是一套 Jupyter 笔记本，包含《Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow》（O'Reilly 出版）第二版的示例代码和练习答案。
这是一个库，还是只是一些教程？它不是可以导入到你自己项目中的软件库，而是一套供你运行并按章节学习的教学用 Jupyter 笔记本。
我该怎么运行这些笔记本？克隆仓库，运行 'conda env create -f environment.yml'，激活 'tf2' 环境，注册 Jupyter 内核，然后启动 'jupyter notebook'。你也可以通过 Colab 或 Kaggle 直接在线打开笔记本，无需安装任何东西，或者使用所提供的 Docker 镜像。
开始之前我需要安装什么？你需要安装 Anaconda 或 Miniconda 以及 git；如果你有兼容 TensorFlow 的 GPU，还需要 GPU 驱动以及与之匹配的 CUDA 和 cuDNN 版本。推荐使用 Python 3.8。
这一版还是最新的吗？不是，这个仓库明确标注为已过时：它是 2019 年的第二版材料，作者建议读者使用 'handson-ml3' 学习当前版本。
代码涵盖哪些主题？这些笔记本涵盖机器学习基础，以及基于 scikit-learn、Keras 和 TensorFlow 的实践示例，与书中的章节相对应。
我可以不安装任何东西就试用吗？可以，你可以通过 Colab 或 Kaggle 等服务在线打开并运行笔记本，这些平台还提供免费的 GPU/TPU。不过这些环境是临时的，因此你要把重要的内容下载保存下来。
我应该用这个还是新版？作者推荐改用 'handson-ml3'，因为这个第二版仓库已不再维护，主要仅作参考保留。
它提供基于 Docker 的安装方式吗？提供。仓库中包含一个 docker 目录，里面有在 Docker 镜像中运行笔记本的说明，无需在本地安装 Anaconda。
What are similar projects?handson-ml, machine-learning-zoomcamp, handson-ml3, 100-Days-Of-ML-Code, cheatsheets-ai, python-machine-learning-book, data-science-ipython-notebooks, TensorFlow-Examples
Which topics is it in?keras, beginner, scikit-learn, numpy, tensorflow, course, neural-network, jupyter notebook, data-science, book, artificial-intelligence, git
Creator
ageron
Size
151.7 MB
Stars
29.9K
Updated
CommitMay 19
Age
7y
Commits · 90 Days