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Apache Kafka vs. Middleware (MQ, ETL, ESB) – Slides + Video

This post shares a slide deck and video recording of the differences between an event-driven streaming platform like Apache Kafka and middleware like Message Queues (MQ), Extract-Transform-Load (ETL) and Enterprise Service Bus (ESB).
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Apache Kafka and Machine Learning
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Apache Kafka + KSQL + TensorFlow for Data Scientists via Python + Jupyter Notebook

Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
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Deep Learning KSQL UDF for Streaming Anomaly Detection of MQTT IoT Sensor Data

KSQL UDF for sensor analytics. Leverages the new API features of KSQL to build UDF / UDAF functions easily with Java to do continuous stream processing with Apache Kafka. Use Case: Connected Cars – Real Time Streaming Analytics using Deep Learning.
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Model Serving: Stream Processing vs. RPC / REST with Java, gRPC, Apache Kafka, TensorFlow

Machine Learning / Deep Learning models can be used in different ways to do predictions. Natively in the application or hosted in a remote model server. Then you combine stream processing with RPC / Request-Response paradigm. This blog post shows examples of stream processing vs. RPC model serving using Java, Apache Kafka, Kafka Streams, gRPC and TensorFlow Serving.
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KSQL Deep Dive – The Open Source Streaming SQL Engine for Apache Kafka

KSQL is the open source, Apache 2.0 licensed streaming SQL engine on top of Apache Kafka. This post shows a deep dive (slides + video recording) including its relation to Kafka Connect and Kafka Streams, concepts, architecture and deployment options.
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