Webinar

Accelerate and Simplify Data Science Workflow with KNIME and H2O Driverless AI

October 27, 2020 - Online

Our partner, H2O.ai, is hosting a webinar to share the details and benefits of the recent integration of H2O.ai and KNIME, which enables enterprises to create more accurate predictions and reduce time to value when implementing data science projects.

Preparing data for AI, selecting the right model, pushing it into production, and continuously optimizing it is a process that typically requires many stakeholders and several tools. Parts of it can be automated but flexibility is essential for selecting the techniques that answer a company’s questions in the best way.

The lack of end-to-end tooling prevalent in most data practices also makes it difficult to ensure data lineage. This H2O.ai and KNIME integration provides a solution that covers these challenges as well as increases data scientists’ productivity, reduces overall IT spend, and creates and uses more accurate predictions.

See this integration in action in a live demo and find out more about the benefits available to customers, specifically:

  • Enable fast, reliable, and flexible access to data, insights, and predictions in enterprise data
  • Build a single integrated visual data science workflow from data preparation to AutoML and to model production
  • Simplify and speed up machine learning with the power of H2O Driverless AI automatic machine learning to business analysts in KNIME Analytics Platform and KNIME Server
  • Productionize H2O Driverless AI models(MOJO) using KNIME drag and drop canvas for model management and monitoring
FAQ
How do I join the webinar?

You’ll receive a zoom link with your registration confirmation. Make sure you have a stable internet connection!

Will I be able to ask questions?

Absolutely - fire away!

Where do I find the latest version of KNIME Analytics Platform?

Download the latest free, open source version of knime here: knime.com/download

What other resources will help me to get started in KNIME?
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