Apache Mahout

Apache Mahout: Open Source Machine Learning Framework

Apache Mahout is an open source machine learning framework for building scalable machine learning applications. It implements distributed or otherwise scalable machine learning algorithms focused primarily on areas like collaborative filtering, clustering and classification.

What is Apache Mahout?

Apache Mahout is an open source machine learning framework aimed at building scalable machine learning applications. Some key aspects of Apache Mahout include:

• Implemented on top of Apache Hadoop to leverage its scalable and distributed capabilities
• Focused on areas like collaborative filtering, clustering and classification out of the box
• Provides Java libraries to allow developers to quickly create scalable machine learning algorithms
• Aims to be agnostic to the underlying execution engine, allowing algorithms to run on various distributed platforms like Apache Spark
• Offers mathematical abstractions to allow reuse of core algorithms across different use cases
• Built to scale linearly with increasing data sizes

Some common use cases of Apache Mahout include building recommender systems, user modeling, categorizing documents, identifying groups of similar documents in a corpus, object recognition and more. Overall it serves as a helpful framework for taking machine learning approaches and making them work on Big Data environments in a scalable fashion.

Apache Mahout Features

Official Links