by Angela Guess

A recent press release reports, “The Apache Software Foundation (ASF), the all-volunteer developers, stewards, and incubators of more than 350 Open Source projects and initiatives, announced today the availability of Apache® Mahout v0.13.0, the latest version of the Open Source scalable machine learning library. Apache Mahout provides an environment for quickly creating machine-learning applications that scale and run on the highest-performance parallel computation engines available. Mahout is the first scalable generalized tensor and linear algebra solving engine taking data scientists from interactive experiments to production use. ‘Apache Mahout 0.13.0 is more powerful with its new algorithm framework that allows for easier implementation of machine learning algorithms,’ said Andrew Palumbo, Vice President of Apache Mahout. ‘The enhanced Mahout code base and development framework make machine learning even more accessible, which is a game changer in the field of artificial intelligence’.”

The release goes on, “Mahout provides a wide variety of premade algorithms (Matrix Factorization, QR via ALS, SSVD, PCA, etc.) for Scala + Apache Spark, H2O, and Apache Flink, as well as on-GPU compute for performance improvements in very large tensor math. Apache Mahout provides the data science tools to automatically find meaningful patterns in Big Data sets by supporting the following main data science use cases: Collaborative filtering – mines user behavior and makes product recommendations (such as eCommerce product recommenders); Regression – estimates a numerical value based on values of other inputs; Clustering – takes items in a particular class (such as Web pages or newspaper articles) and organizes them into naturally occurring groups, such that items belonging to the same group are similar to each other; and Classifying – learns from existing categorizations and then assigns unclassified items to the best category.”

Read more at Globe Newswire.

Photo credit: ASF