Machine Learning on Source Code

Explore the emerging field of Machine Learning on Source Code (MLoSC) in this 34-minute conference talk from ML Conference 2018. Discover how this innovative domain combines deep learning, natural language processing, social science, and programming to unlock the potential of vast amounts of open-source code data. Learn about current trends in MLoSC and gain insights into tools and applications such as deep code suggestions, structural embeddings for fuzzy deduplication, and machine learning at the pull request level. Understand how these advancements can improve developers' daily lives and provide valuable insights into software projects. Presented by Egor Bulychev from source|{d}, this talk offers an introduction to the exciting possibilities of applying machine learning techniques to source code analysis and development.

Machine Learning on Source Code | Egor Bulychev | ML Conference 2018