Contribute

Note

_images/logo_lGPL.png

Mapping Learning is a free, open-source application, distributed under the lGPL v3 license. Feel free to contribute !

You do not have to know how to code, you can contribute by:

  • Using it
  • Tracing the issues or proposing improvements on the bug tracker
  • Improving documentation

Feel free to contact me (alban.thomas@univ-rennes2.fr).

Documentation

The documentation is built from the source code (using sphinx) and is available in PDF, epub and HTML. Up-to-date documentation is available at https://maplearn.readthedocs.io/en/latest/ .

Source code

_images/logo_python.png

Maplearn is written in Python. The source code is available at https://bitbucket.org/thomas_a/maplearn/src/master/. You can simply download a copy from this link but using git you can easily get updates.

git clone https://bitbucket.org/thomas_a/maplearn.git
# then, to get updates
git pull

Philosophy

Wondering what you can expect from Mapping Learning software? The few points below give the “philosophy” of the software:

  • Mapping Learning should be able to be used as you wish (freedom)

Mapping Learning is usable whatever your environment (Windows, Linux or Mac) and the way you want (graphical or online interface of commands, or even write a Python script).

  • Mapping Learning should help you to learn machine learning (knowledge base)

We learn from our mistakes. Mapping Learning will not prevent you from making meaningless predictions but must help you to realize you are doing it wrong (through advice, warnings …).

  • Mapping Learning should help you to understand your data (visualization)

Data visualization really matters. Mapping Learning will integrate all possible means (not just graphics) to better understand your data and results.

  • Mapping Learning should be useful to everyone (openness)

Mapping Learning was initially dedicated to remote sensing, but the applications of machine learning are much larger. Maplearn allows you to use your data whether they are geographic or not (text files, Excel, and more to come).

  • Mapping Learning should be up to date

Machine Learning evolves quickly and Mapping Learning will try to give you access to the latest algorithms.

  • Mapping Learning is about machine learning and only machine learning

Mapping Learning is not a GIS or data manipulation software (ETL). Very good software already exists.