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Lecture: Machine Learning on Source Code

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Machine Learning on Source Code (MLonCode) is an emerging and exciting domain of research which stands at the sweet spot between deep learning, natural language processing, social science and programming. The list of MLonCode resources - awesome-machine-learning-on-source-code - has already attracted more than 1,700 watchers on GitHub.

I will summarize the current research subdomains in MLonCode, such as identifier and structural embeddings, programming language modeling, automated programming language evolution and source code topic modeling and exploratory search. I will also describe the open MLonCode toolbox from source{d} based on PySpark: sourced.engine and It provides an in-depth set of Python APIs and command line applications which is already being used for various production tasks. Finally, I will show how to apply that toolbox to analyze all world's Python open source code and mine gems.


Day: 2018-05-04
Start time: 12:00
Duration: 00:30
Room: F0.01
Track: PyDays
Language: en




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