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[P] Open source library to perform entity embeddings on categorical variables using Convolutional Neural Networks [+ Unit Tests, Code Coverage and Continuous Integration]

In the past 2 years I have been working as a Machine Learning developer, mostly with tabular data, and I’ve developed a tool to perform entity embeddings on categorical variables using CNN with Keras. I tried pretty much to make it easy to use and flexible to most of the existent scenarios (regression, binary and multi-class classification), but if you find any other need or issue to be fixed, do not hesitate to ask.

I tried to add some cool stuff on the project, such as unit tests, code coverage with Codacy, continuous integration with Travis CI and auto deployment to PyPi and auto-generated documentation with Sphinx and ReadTheDocs, so if any of you is interested in how to setup your project to have these features, feel free to use it as a base project.

Looking forward to any reviews about the source code. Any tip to improve the readability or even performance, its really welcome and well appreciated.

Github: https://github.com/bresan/entity_embeddings_categorical

PyPi: https://pypi.org/project/entity-embeddings-categorical/

Code coverage (nowadays reaching 97%): https://coveralls.io/github/bresan/entity_embeddings_categorical?branch=master

Thanks and I hope it can help somebody out there 🙂

submitted by /u/CrazyCapivara
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.