Machine Learning on Source Code
Offered By: MLCon | Machine Learning Conference via YouTube
Course Description
Overview
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.
Syllabus
Machine Learning on Source Code | Egor Bulychev | ML Conference 2018
Taught by
MLCon | Machine Learning Conference
Related Courses
Why Security Is Important in ML and How To Secure Your ML-based SolutionsMLCon | Machine Learning Conference via YouTube Using A.I to Make Recommendations for Career Progression
MLCon | Machine Learning Conference via YouTube Kotlin for Machine Learning
MLCon | Machine Learning Conference via YouTube Honey, I Shrunk the TinyML
MLCon | Machine Learning Conference via YouTube Using Predictive Analytics and Machine Learning
MLCon | Machine Learning Conference via YouTube