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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Oct 16, 2020 | 10:00 am PT / 1:00 pm ET