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⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
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| 2026-09-18 | 25605 |
| 2026-09-19 | 25606 |
| 2026-09-20 | 25605 |
Today
-1 stars today
This week
— stars this week
This month
+8 stars this month
Momentum
0.0
growth rate 0.00%/day
Machine Learning Notebooks
==========================
# ⚠ THE <a href="https://github.com/ageron/handson-ml3">THIRD EDITION OF MY BOOK</a> IS NOW AVAILABLE, AS WELL A <a href="https://github.com/ageron/handson-mlp">PYTORCH VERSION</a> AND <a href="https://homl.info/">MANY TRANSLATIONS</a>.
This project is for the first edition, which is now outdated (it came out in 2017).
<details>
This project aims at teaching you the fundamentals of Machine Learning in
python. It contains the example code and solutions to the exercises in my O'Reilly book [Hands-on Machine Learning with Scikit-Learn and TensorFlow](https://learning.oreilly.com/library/view/hands-on-machine-learning/9781491962282/):
[](https://learning.oreilly.com/library/view/hands-on-machine-learning/9781491962282/)
## Quick Start
### Want to play with these notebooks online without having to install anything?
Use any of the following services.
**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.
* **Recommended**: open this repository in [Colaboratory](https://colab.research.google.com/github/ageron/handson-ml/blob/master/):
<a href="https://colab.research.google.com/github/ageron/handson-ml/blob/master/"><img src="https://colab.research.google.com/img/colab_favicon.ico" width="90" /></a>
* Or open it in [Binder](https://mybinder.org/v2/gh/ageron/handson-ml/master):
<a href="https://mybinder.org/v2/gh/ageron/handson-ml/master"><img src="https://matthiasbussonnier.com/posts/img/binder_logo_128x128.png" width="90" /></a>
* _Note_: Most of the time, Binder starts up quickly and works great, but when handson-ml is updated, Binder creates a new environment from scratch, and this can take quite some time.
* Or open it in [Deepnote](https://beta.deepnote.com/launch?template=data-science&url=https%3A//github.com/ageron/handson-ml/blob/master/index.ipynb):
<a href="https://beta.deepnote.com/launch?template=data-science&url=https%3A//github.com/ageron/handson-ml/blob/master/index.ipynb"><img src="https://www.deepnote.com/static/illustration.png" width="150" /></a>
### Just want to quickly look at some notebooks, without executing any code?
Browse this repository using [jupyter.org's notebook viewer](https://nbviewer.jupyter.org/github/ageron/handson-ml/blob/master/index.ipynb):
<a href="https://nbviewer.jupyter.org/github/ageron/handson-ml/blob/master/index.ipynb"><img src="https://jupyter.org/assets/logos/rectanglelogo-greytext-orangebody-greymoons.svg" width="150" /></a>
_Note_: [github.com's notebook viewer](index.ipynb) also works but it is slower and the math equations are not always displayed correctly.
### Want to run this project using a Docker image?
Read the [Docker instructions](https://github.com/ageron/handson-ml/tree/master/docker).
### Want to install this project on your own machine?
Start by installing [Anaconda](https://www.anaconda.com/distribution/) (or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)), [git](https://git-scm.com/downloads), and if you have a TensorFlow-compatible GPU, install the [GPU driver](https://www.nvidia.com/Download/index.aspx), 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-ml.git
$ cd handson-ml
Next, run the following commands:
$ conda env create -f environment.yml
$ conda activate tf1
$ python -m ipykernel install --user --name=python3
Finally, start Jupyter:
$ jupyter notebook
If you need further instructions, read the [detailed installation instructions](INSTALL.md).
# FAQ
**Which Python version shExcerpt of 5,869 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e7630a5c05b89eb8, topic:deep-learning, topic:neural-network, topic:tensorflow