Watch this webinar to see Splice Machine’s ML Manager in action and learn how you can operationalize machine learning from development to deployment on a unified operational, analytical and machine learning platform.

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Webinar: Operationalize Machine Learning from Development to Deployment

Traditional data infrastructure consisting of separate operational, analytical and data science platforms does not provide a viable foundation to power mission-critical machine learning (ML) applications. This architecture has latency built-in at multiple levels. In this webinar, Gene Davis, Splice Machine co-founder and VP of Product Management, will present how native ML capability built into a unified operational and analytical data platform can greatly enhance an enterprise’s ability to inject AI/ML into their mission critical applications.

In this webinar, Gene will demonstrate how data science teams can be more effective with Splice Machine’s ML Manager by:

  • Experimenting with many diverse models to optimize business decisions
  • Leveraging in-the-moment operational data to train and apply the model
  • Reducing the burden of data movement by leveraging Splice Machine's Native Spark DataSource
  • Compressing the time from model development to deployment

Using ML Manager, organizations can easily harness the power of operational AI to deliver mission-critical applications faster across a variety of industries, including financial services, healthcare, and manufacturing.