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# Kafka-ML: connecting the data stream with ML/AI frameworks

Kafka-ML is a framework to manage the pipeline of Tensorflow/Keras and PyTorch (Ignite) machine learning (ML) models on Kubernetes. The pipeline allows the design, training, and inference of ML models. The training and inference datasets for the ML models can be fed through Apache Kafka, thus they can be directly connected to data streams like the ones provided by the IoT.
Kafka-ML provides a comprehensive framework for efficiently managing the pipeline of machine learning models built on Tensorflow/Keras and PyTorch (Ignite) in a Kubernetes environment. This pipeline is designed to support the complete lifecycle of ML models, from their inception to training and inference.

ML models can be easily defined in the Web UI with no need for external libraries and executions, providing an accessible tool for both experts and non-experts on ML/AI.

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