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About the talk: It has become very easy to create, publish, and collect data in digital form. The volume of structured and unstructured data is increasing at tremendous pace. This has led to a whole new set of applications that can be build if one solves the problem of turning raw data into valuable information. Possible applications include but are not limited to: Discovering new trends from a stream of weblog entries. Automatic learning approaches for supplementing market research processes for new products. Machine learning provides tools for building such applications. A large community of researchers has been working on the topic of learning from data. Although a lot of information on algorithms and solutions to common problems are publicly available, scaling these solutions into the range of terabytes and petabytes is an open issue. To scale algorithms to such dimensions it is indispensable to distribute data as well as computation. The mission of the Mahout project is to build a suite of scalable machine learning algorithms that can cope with todays amount of data. The project is built on top of Hadoop. This talk provides a beginner-friendly introduction to the topic of machine learning. It presents a broad set of applications that benefit machine learning. The presentation gives a highlevel overview of the project itself: The types of tasks that can be solved with each algorithm and the pitfalls one needs to look out for when using it.
Speaker Bio: Isabel Drost co-founded the Lucene sub-project Apache Mahout. She is employed at the neofonie GmbH, a company building enterprise search engines. Isabel has interned at Google for six months in 2005/06. She worked as research assistant in Berlin. Isabel holds a master's degree in computer science from the University of Applied Sciences Mittweida.
Links
* http://us.apachecon.com/c/acus2009/schedule/2009/11/06
* http://us.apachecon.com/c/acus2009/speakers/288
* http://us.apachecon.com/c/acus2009/sessions/333
* http://lucene.apache.org/mahout
* http://hadoop.apache.org
* http://www.isabel-drost.de
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