Resources & Documentation

This project will require experimentation with several different machine learning libraries and environments within Python. This page serves as a collection of resources that we found helpful in our research and experimenation.

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Programming Resources:

Python Sci-kit learn: http://scikit-learn.org/stable/modules/neural_networks_supervised.html

Scaling sci-kit learn to GPU enabled systems: http://scikit-learn.org/stable/related_projects.html#related-projects

Neural nets in sci-kit learn: http://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html

Sci-kit learn precision and recall: http://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_fscore_support.html

Sci-kit learn accuracy: http://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html