kafka-streams-machine-learning-examples and tensorflow-serving-java-grpc-kafka-streams
About kafka-streams-machine-learning-examples
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.
About tensorflow-serving-java-grpc-kafka-streams
kaiwaehner/tensorflow-serving-java-grpc-kafka-streams
Kafka Streams + Java + gRPC + TensorFlow Serving => Stream Processing combined with RPC / Request-Response
This project helps operations engineers and data scientists integrate real-time machine learning predictions into their data streams. It takes incoming data from Apache Kafka, sends it to an external TensorFlow model for predictions, and then outputs the enriched data back into a Kafka stream. This is ideal for scenarios where you need to leverage advanced model management features while processing high volumes of streaming data.
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