mPyPl: Python Monadic Pipeline Library for Complex Functional Data Processing
- Programming / Tools
- Data Science, Big Data
- Accepted
November 14, 15:45
Room II|II зал
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We present a library for complex functional data processing in Python called mPyPl (Monadic Pipeline Library). We discuss the motivation, main principles, as well as real-world cases of using the library in complex machine learning tasks of event detection in videos.
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Dmitri Soshnikov
Senior Software Engineer, Microsoft
Dmitri has been working in Microsoft for 13 years, originally as Technical Evangelist, and lately as a Software Engineer in Commercial Software Engineering team, where he has helped many customers accross the workd to use AI/ML technologies to improve their business. His main expertise is AI and Computer Vision, and also Functional Programming. He teaches courses on AI and Functional Programming at MIPT, HSE and MAI.
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