alphapy

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

Showing:

Popularity

Downloads/wk

0

GitHub Stars

629

Maintenance

Last Commit

7mos ago

Contributors

3

Package

Dependencies

17

License

Apache License, Version 2

Categories

Readme

AlphaPy

|badge_pypi| |badge_build| |badge_docs| |badge_downloads|

AlphaPy is a machine learning framework for both speculators and data scientists. It is written in Python mainly with the scikit-learn and pandas libraries, as well as many other helpful packages for feature engineering and visualization. Here are just some of the things you can do with AlphaPy:

  • Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost.
  • Generate blended or stacked ensembles.
  • Create models for analyzing the markets with MarketFlow.
  • Predict sporting events with SportFlow.
  • Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio.

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/model_pipeline.png :width: 100% :alt: AlphaPy Model Pipeline :align: center

Documentation

http://alphapy.readthedocs.io/en/latest/

Installation

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy::

pip install -U alphapy

Pyfolio


Pyfolio is automatically installed by AlphaPy, but if you encounter
the following error when trying to create a tear sheet:

    *AttributeError: 'numpy.int64' object has no attribute 'to_pydatetime'*

Install pyfolio with this command:

    pip install git+https://github.com/quantopian/pyfolio

XGBoost

For Mac and Windows users, XGBoost will not install automatically with pip. For instructions to install XGBoost on your specific platform, go to http://xgboost.readthedocs.io/en/latest/build.html.

LightGBM


For instructions to install LightGBM on your specific
platform, go to https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html.

CatBoost

For instructions to install CatBoost on your specific platform, go to https://catboost.ai/docs/concepts/python-installation.html.

MarketFlow

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/market_pipeline.png :width: 100% :alt: MarketFlow Model :align: center

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/system_pipeline.png :width: 100% :alt: MarketFlow System :align: center

SportFlow

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/sports_pipeline.png :width: 100% :alt: SportFlow :align: center

Support

The official channel for support is to open an issue on Github.

http://github.com/ScottfreeLLC/AlphaPy/issues

Follow us on Twitter:

https://twitter.com/_AlphaPy_?lang=en

Donations

If you like the software, please donate:

http://alphapy.readthedocs.io/en/latest/introduction/support.html#donations

.. |badge_pypi| image:: https://badge.fury.io/py/alphapy.svg .. |badge_build| image:: https://travis-ci.org/ScottfreeLLC/AlphaPy.svg?branch=master .. |badge_docs| image:: https://readthedocs.org/projects/alphapy/badge/?version=latest .. |badge_downloads| image:: https://pepy.tech/badge/alphapy

Rate & Review

Great Documentation0
Easy to Use0
Performant0
Highly Customizable0
Bleeding Edge0
Responsive Maintainers0
Poor Documentation0
Hard to Use0
Slow0
Buggy0
Abandoned0
Unwelcoming Community0
100