Skip to main content

GossipCat, A Cat Who Is Always Gossiping.

Project description

https://badge.fury.io/gh/ewen2015%2Fgossipcat.svg https://img.shields.io/badge/License-Apache%202.0-blue.svg https://badge.fury.io/py/gossipcat.svg https://img.shields.io/pypi/pyversions/gossipcat.svg

πŸ˜ΈπŸ˜ΉπŸ˜ΊπŸ˜»πŸ˜ΌπŸ˜½πŸ˜ΎπŸ˜ΏπŸ™€πŸ±

GossipCat is a machine learning framework that simplifies the process of machine learning from data cleaning, simple feature engineering, hyper parameter tuning, to results output. It is designed to be efficient with the following features:

  • Combines feature engineering and hyper parameter tuning.
  • Automates feature engineering and hyper parameter tuning with algorithms.
  • Provides accesses of the most efficient machine learning algorithm.

Story of the GossipCat

The package names after a cat of my friend, LEEverpool. Actually, the GossipCat is the name of a WeChat group, where my friends gossip there.

https://raw.githubusercontent.com/Ewen2015/GossipCat/master/GossipCat.jpeg

License

GossipCat is licensed under the Apache License 2.0. Β© Contributors, 2018.

A permissive license whose main conditions require preservation of copyright and license notices. Contributors provide an express grant of patent rights. Licensed works, modifications, and larger works may be distributed under different terms and without source code.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
gossipcat-0.1.76-py3-none-any.whl (37.2 kB) Copy SHA256 hash SHA256 Wheel py3

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page