Apache Mahout, an open-source project from the Apache Software Foundation that has significantly evolved from a MapReduce-based machine learning library to focus on providing a Scala DSL for scalable linear algebra, primarily leveraging Apache Spark as its distributed backend. Mahout excels in areas like recommendation systems, including a unique Correlated Co-Occurrence algorithm, and dimensionality reduction techniques.

However, many older algorithms are deprecated, and the project's recent strategic direction is heavily influenced by Qumat, an initiative focused on quantum computing. The text details Mahout's architecture, key components like Distributed Row Matrices (DRMs), performance enhancements, and compares it to alternatives like Spark MLlib and Scikit-learn.