wechinelearn 0.0.1

Weather data based machine learning R&D framework

Welcome to wechinelearn Documentation

wechinelearn is a Weather data based machine learning R&D framework. Basically, if you want to use weather data to build a classification/prediction model, this framework could help.

The first major problem in model R&D is handling big dataset. wechinelearn can use any relational database as back-end, and easy to extend for adding more data or data point. Using database can greatly reduce the average time cost for trying your idea.

Your target object, could be a user, a region or anything associated with local weather by location. One major problem wechinelearn solved is finding best weather data for your target, and also takes missing data points, unreliable data points, multiple data source choice into account.

Quick Links

• GitHub Homepage

• Online Documentation

• PyPI download

• Install

• Issue submit and feature request

• API reference and source code

Install

wechinelearn is released on PyPI, so all you need is:

$ pip install wechinelearn

To upgrade to latest version:

$ pip install --upgrade wechinelearn

If you have problem with installing numpy in Windows, download the compiled wheel file here, and install it with pip.