Build and operationalize machine learning models

Seamless training, testing, scoring, and model management with StreamAnalytix

Download this white paper to learn:

  • Advantages and use cases of machine learning (ML) across industries
  • Training and deployment of ML models using StreamAnalytix
  • Model management using StreamAnalytix
  • How to operationalize models using StreamAnalytix

Enterprises use ML for its advantages like high-speed data processing, real-time insights, consistent decision-making, reusability, and extensibility across use cases like:

This paper details how you can build, train, test, score, manage, and operationalize ML models using StreamAnalytix – a self-service ETL and analytics tool. The platform helps enterprises create batch and streaming ETL pipelines using drag-and-drop operators on a visual IDE. It has a wide array of built-in operators for data sources, transformations, ML, and data sinks.

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