kaiwaehner/kafka-streams-machine-learning-examples
This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
This project offers examples for deploying trained machine learning models into live production systems. It shows how to take models created with tools like TensorFlow or H2O and integrate them with Apache Kafka's Streams API to process real-time data. Data engineers, MLOps specialists, or software architects who need to operationalize machine learning models for mission-critical applications would use this.
909 stars. No commits in the last 6 months.
Use this if you need to integrate machine learning predictions into high-throughput, real-time data streams for applications like fraud detection or predictive maintenance.
Not ideal if you are looking for guidance on how to train or build machine learning models, as this project focuses solely on deployment.
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909
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317
Language
Java
License
Apache-2.0
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Last pushed
Dec 17, 2023
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