pDB: Abstraction for Modeling Predictive Machine Learning Problems
884 views · Published 15 June 2018 · 8:50 · Indexed 24 October 2026
Channel: InfoQ · 2018 · Science & Technology
Balaji Rengarajan does a brief overview of modeling machine learning problems using Celect’s pDB framework. He demonstrates how disparate predictive problems can be expressed using a common pDB language. Balaji Rengarajan is responsible for architecting and engineering key aspects of the cloud- agnostic data science platform based on Celect’s pDB framework for non-parametric machine learning. This video was recorded at QCon.ai 2018: https://bit.ly/2piRtLl More videos from QCon.ai 2018 on InfoQ: https://bit.ly/2rNAT8z The InfoQ Architects' Newsletter is your monthly guide to all the topics, technologies and techniques that every professional or aspiring software architect needs to know about. Over 200,000 software architects, team leads, CTOs are subscribed to it. Sign up here: https://bit.ly/2KqYfrs
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