Train models

Note

The managed MLflow integration with Databricks on Google Cloud requires Databricks Runtime for Machine Learning 8.1 or above.

This section covers how to train machine learning and deep learning models on Databricks, and includes examples using many popular libraries. You can also use Databricks AutoML, which automatically prepares a dataset for model training, performs a set of trials using open-source libraries such as scikit-learn and XGBoost, and creates a Python notebook with the source code for each trial run so you can review, reproduce, and modify the code.