Using Apache Kafka to Drive Cutting-Edge Machine Learning | Confluent
Nov 19, 2018Kai Waehner
Summary
This post introduces the concept of embedding ML models directly into Kafka Streams or KSQL applications, or deploying them to dedicated model servers. It details the tradeoffs of each approach, discusses hybrid cloud architectures for training and inference, and highlights the use of KSQL for preprocessing and embedding ML models via user-defined functions (UDFs).
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