https://github.com/glemaitre/pyparis-2018-sklearn

PyParis tutorial on machine learning using scikit-learn
https://github.com/glemaitre/pyparis-2018-sklearn

data-science machine-learn pandas scikit-learn

Last synced: 2 months ago
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PyParis tutorial on machine learning using scikit-learn

• Host: GitHub
• URL: https://github.com/glemaitre/pyparis-2018-sklearn
• Owner: glemaitre
• License: cc0-1.0
• Created: 2018-11-08T15:30:37.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-11-22T02:18:34.000Z (about 1 year ago)
• Last Synced: 2024-10-23T12:19:52.135Z (3 months ago)
• Topics: data-science, machine-learn, pandas, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 648 KB
• Stars: 74
• Watchers: 5
• Forks: 19
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PyParis 2018: Machine learning using scikit-learn

### Instructors

* Guillaume Lemaitre - Inria, Paris-Saclay Center for Data Science

* Jeremie du Boisberranger - scikit-learn @ fondation Inria

* Joris Van den Bossche - Inria, Paris-Saclay Center for Data Science

* and others to come ...

### Obtaining the Tutorial Material

If you have a GitHub account, it is probably most convenient if you clone or

fork the GitHub repository. You can clone the repository by running:

```bash

git clone https://github.com/glemaitre/pyparis-2018-sklearn.git

```

If you are not familiar with git or don't have an GitHub account, you can

download the repository as a `.zip` file by heading over to the GitHub

repository (https://github.com/glemaitre/pyparis-2018-sklearn) in your browser

and click the green “Download” button in the upper right.

Please note that we may add and improve the material until shortly before the

tutorial session, and we recommend you to update your copy of the materials one

day before the tutorials. If you have an GitHub account and cloned the

repository via GitHub, you can sync your existing local repository with:

```bash

git pull origin master

```

If you don't have a GitHub account, you may have to re-download the `.zip`

archive from GitHub.

### Requirements

To check if your system have the required libraries, you can execute the

following script:

```bash

python check_environment.py

```

If you are using `conda`, you can create a specific environment for this

tutorial with the following commands:

```bash

conda env create environment.yml

conda activate pyparis_sklearn  # or source activate pyparis_sklearn

```

### References

This material is based on the fruitful work of the `scikit-learn` community and

more broadly to the Pythonista of the whole data science community.