Low-Code Machine Learning

Leverage a low-code approach with Databricks AutoML

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 also domain experts and analysts who can benefit from low-code tools to build ML solutions.

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