Apache Kafka + KSQL + TensorFlow for Data Scientists via Python + Jupyter Notebook

Posted in Analytics, Apache Kafka, Big Data, Confluent, Deep Learning, Integration, Jupyter, Kafka Connect, Kafka Streams, KSQL, Machine Learning, Open Source, Python, Stream Processing, TensorFlow on January 18th, 2019 by Kai Wähner

Why would a data scientist use Kafka Jupyter Python KSQL TensorFlow all together in a single notebook?

There is an impedance mismatch between model development using Python and its Machine Learning tool stack and a scalable, reliable data platform. The former is what you need for quick and easy prototyping to build analytic models. The latter is what you need to use for data ingestion, preprocessing, model deployment and monitoring at scale. It requires low latency, high throughput, zero data loss and 24/7 availability requirements.

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