Data Wrangling is a blog which covers machine learning algorithms, data mining, mathematical finance, information retrieval, web mashups, and parallel programming. It also includes python and ruby programming tutorials in these areas, along with useful hacks and code snippets.

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Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive, diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come to the mailing lists to find out more.

Move business intelligence to a level of knowledge management with Datawatch. More than data mining software, Datawatch provides information management solutions through enterrpise content management, data and report mining software, training and services. Datawatch and Monarch software assists enterprise or desktop users across industries to securely archive emails, manage employees, and document information.