Weather data based machine learning R&D framework
Project description
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.
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Install
wechinelearn is released on PyPI, so all you need is:
$ pip install wechinelearnTo upgrade to latest version:
$ pip install --upgrade wechinelearnIf you have problem with installing numpy in Windows, download the compiled wheel file here, and install it with pip.
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