Machine Learning

Apache Ignite 2.0 release introduced first version of its own distributed Machine Learning (ML) library called ML Grid.

The rationale for building ML Grid is quite simple. Many users employ Ignite as the central high-performance storage and processing system. If they want to execute ML or Deep Learning (DL) algorithms (i.e training sets or model inference) they can run them directly on Ignite cluster without having to ETL the data into some other system, like Apache Mahout or Apache Spark.

Presently ML Grid supports core distributed algebra implementation based on Ignite co-located distributed processing, as well as other essential machine learning algorithms such as Linear Regression, Decision Trees, K-Means clustering and more. Future releases will introduce custom DSLs for Python, R and Scala, growing collection of optimized ML algorithms as well as support for Ignite-optimized Neural Networks.