https://github.com/jakevdp/sklearn_tutorial

Materials for my scikit-learn tutorial
https://github.com/jakevdp/sklearn_tutorial

Last synced: about 1 month ago
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Materials for my scikit-learn tutorial

• Host: GitHub
• URL: https://github.com/jakevdp/sklearn_tutorial
• Owner: jakevdp
• License: bsd-3-clause
• Archived: true
• Created: 2015-09-08T17:23:32.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2023-03-23T14:14:32.000Z (about 1 year ago)
• Last Synced: 2024-02-07T19:09:36.072Z (5 months ago)
• Language: Jupyter Notebook
• Size: 9.19 MB
• Stars: 1,733
• Watchers: 105
• Forks: 946
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-astrodata - Scikit-Learn Tutorial
• awesome-stars - sklearn_tutorial - Materials for my scikit-learn tutorial (Jupyter Notebook)
• my-awesome-stars - jakevdp/sklearn_tutorial - Materials for my scikit-learn tutorial (Jupyter Notebook)

README

        
# Scikit-learn Tutorial

*Jake VanderPlas*

- email: 

- twitter: [@jakevdp](https://twitter.com/jakevdp)

- github: [jakevdp](http://github.com/jakevdp)

This repository contains notebooks and other files associated with my

[Scikit-learn](http://scikit-learn.org) tutorial.

## Installation Notes

This tutorial requires the following packages:

- Python version 2.6-2.7 or 3.3+

- `numpy` version 1.5 or later: http://www.numpy.org/

- `scipy` version 0.10 or later: http://www.scipy.org/

- `matplotlib` version 1.3 or later: http://matplotlib.org/

- `scikit-learn` version 0.14 or later: http://scikit-learn.org

- `ipython` version 2.0 or later, with notebook support: http://ipython.org

- `seaborn` version 0.5 or later

The easiest way to get these is to use the [conda](https://store.continuum.io/) environment manager.

I suggest downloading and installing [miniconda](http://conda.pydata.org/miniconda.html).

Once this is installed, the following command will install all required packages in your Python environment:

```

Original install (2015)

$ conda install numpy scipy matplotlib scikit-learn ipython-notebook seaborn

Or for current versions of Anaconda (Mar 2018)

 

$ conda create -n skl_tut python=3.4.5 ipywidgets=5.2.2 numpy scipy matplotlib scikit-learn ipython-notebook seaborn pillow

$ activate skl_tut

$ jupyter notebook --notebook-dir=''

```

Alternatively, you can download and install the (very large) Anaconda software distribution, found at https://store.continuum.io/.

## Downloading the Tutorial Materials

I would highly recommend using git, not only for this tutorial, but for the

general betterment of your life.  Once git is installed, you can clone the

material in this tutorial by using the git address shown above:

    git clone git://github.com/jakevdp/sklearn_tutorial.git

If you can't or don't want to install git, there is a link above to download

the contents of this repository as a zip file.  I may make minor changes to

the repository in the days before the tutorial, however, so cloning the

repository is a much better option.

## Notebook Listing

You can [view the tutorial materials](http://nbviewer.ipython.org/github/jakevdp/sklearn_tutorial/blob/master/notebooks/Index.ipynb) using the excellent nbviewer service.

Note, however, that you cannot modify or run the contents within nbviewer.

To modify them, first download the tutorial repository, change to the notebooks directory, and run ``ipython notebook``.

You should see the list in the ipython notebook launch page in your web browser.

For more information on the IPython notebook, see http://ipython.org/notebook.html

Note also that some of the code in these notebooks will not work outside the

directory structure of this tutorial, so it is important to clone the full

repository if possible.