669: Streaming, reactive, real-time machine learning
Super Data Science: ML & AI Podcast with Jon Krohn
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Reactivity in Data Processing
This chapter delves into the concept of reactivity in data processing, highlighting its role in automatically processing data changes without manual intervention. It explores the importance of incrementality and declarative programming in creating reactive systems, as well as the challenges faced by developers in handling real-time data streams and evolving data types. The discussion emphasizes the need for reactive data processing to adapt to feature drift in machine learning models and ensure successful project outcomes.
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