Apache Spark MLlib is the Apache Spark machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives. Azure Databricks recommends the following Apache Spark MLLib guides:
The following notebooks demonstrate how to use various Apache Spark MLlib features using Azure Databricks.
- Binary Classification Example
- Decision Trees Examples
- Apache Spark MLlib Pipelines and Structured Streaming Example
- Advanced Apache Spark MLlib Example
For reference information about MLlib features, Azure Databricks recommends the following Apache Spark API reference:
For using Apache Spark MLlib from R, refer to the R machine learning documentation.
For Azure Databricks support for visualizing machine learning algorithms, see Machine learning visualizations.