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README.md

Python Machine Learning Snippets (pymls)

Python Machine Learning Snippets (pymls) is my ongoing pet project where I try out different machine learning models. This project contains various machine learning examples as Jupyter notebooks with scikit-learn, statsmodel, numpy and other libraries.

Note: This is an ongoing project and far away from complete.

Getting Started

All the required Python packages can be installed with pipenv.

Project Setup

First you nee to install pipenv.

$ pip install --user pipenv

Install all the required packages

$ pipenv install --dev

Run the Notebook

You can start jupyter-lab to play around with the Juypter notebooks.

pipenv run jupyter-lab

Run the Tests (nbval)

To test the Jupyter notebooks this project uses nbval, which is a py.test plugin for validating Jupyter notebooks.

This will check all Jupyter notebooks for errors.

pipenv run py.test --nbval-lax

Upgrade Python Packages

Check which packages have changed.

pipenv update --outdated

This will upgrade everything.

pipenv update

CI Build (GitHub Actions)

See the GitHub Actions build.yml file for more details. CI Build

Export the Jupyter Notebooks

To export the Jupyter notebooks to Markdonw the export-notebooks.sh script can be used. This scrip uses nbconvert to convert the Jupyter notebooks.

The Snippets...

The following machine learning snippets are available as Jupyter Notebook.

About

Python Machine Learning Snippets (pymls) contains various machine learning examples as Jupyter notebooks with scikit-learn, statsmodel, numpy and other libraries.

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