Operationalize machine learning and data science for better business outcomes

Build and Operationalize Machine Learning Models

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Data science and machine learning (ML) tools have gained rapid recognition for their ability to accelerate analytical insight and improve the efficiency of your business processes.

But while you might know you want to deploy ML tools to solve specific problems, like improving decision making or processing data in real time, it’s not always easy to deploy ML tools with your existing data architectures.

Read on to learn how you can better operationalize your data science and ML models by better integrating them, setting them up to be run at scale, improving monitoring, and more.

Vendor:
StreamAnalytix
Posted:
13 Oct 2020
Published:
13 Oct 2020
Format:
PDF
Type:
White Paper
Language:
English
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