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Low-Code Machine Learning on Databricks with AutoML

On Demand

Type

  • Session

Format

  • Hybrid

Track

  • Data Science, Machine Learning and MLOps

Room

  • Moscone South | Level 3 | 306

Duration

  • 35 min
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Overview

Teams across an organization should be able to use predictive analytics for their business. While there are data scientists and data engineers who can leverage code to build ML models, there are domain experts and analysts who can benefit from low-code tools to build ML solutions.

Join this session to learn how you can leverage Databricks AutoML and other low-code tools to build, train and deploy ML models into production. Additionally, Databricks takes a unique glass-box approach, so you can take the code behind ML model and tweak further to fine-tune performance and integrate into production systems. See these capabilities in action and learn how Databricks empowers users of varying levels of expertise to build ML solutions.

Session Speakers

Headshot of Stephanie Rivera

Stephanie Rivera

Solutions Architect

Databricks

Headshot of Nicolas Pelaez

Nicolas Pelaez

Technical Marketing DS/ML

Databricks

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