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In this Databricks tutorial you will learn the Databricks Machine Learning Workspace basics for beginners. Databricks Machine Learning is an integrated end-to-end machine learning environment incorporating managed services for experiment tracking, model training, feature development and management, and feature and model serving.

With Databricks Machine Learning, you can:
+ Train models either manually or with AutoML
+ Track training parameters and models using experiments with MLflow tracking
+ Create feature tables and access them for model training and inference
+ Share, manage, and serve models using Model Registry

You also have access to all of the capabilities of the Databricks workspace, such as notebooks, clusters, workflows, data, Delta tables and security and admin controls.

Visit the Databricks docs to learn more:
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Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. [ Ссылка ]

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