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Learning Apache Mahout

You're reading from  Learning Apache Mahout

Product type Book
Published in Mar 2015
Publisher
ISBN-13 9781783555215
Pages 250 pages
Edition 1st Edition
Languages

About the Reviewers

Saleem A. Ansari is a full-stack Java, Scala, and Ruby developer with over 7 years of industry experience and a special interest in machine learning and information retrieval. Having implemented the data ingestion and processing pipeline in Core Java and Ruby separately, he knows the challenges faced by huge datasets in such systems. He has worked for companies such as Red Hat, Impetus Technologies, Belzabar Software, and Exzeo Software. He is also a passionate member of the Free and Open Source Software (FOSS) community. He started his journey with FOSS in 2004. The very next year, 2005, he formed JMILUG, a Linux user group at Jamia Millia Islamia University, New Delhi. Since then, he has been contributing to FOSS by organizing community activities and contributing code to various projects (such as github.com/tuxdna). He also advises students about FOSS and its benefits. He is currently enrolled at Georgia Institute of Technology, USA, for the MSCS program. He can be reached at . He maintains a blog at http://tuxdna.in/.

Sahil Kharb is the computer science undergraduate student at Indian Institute of Technology, Jodhpur (India). He has been working on Mahout and Hadoop for the last 2 years. His area of interest is data mining on a large scale. Nowadays, he works on Apache Spark and Apache Storm, doing real-time data analytics and batch processing with the help of Apache Mahout.

Pavan Kumar Narayanan is an applied mathematician with experience in mathematical programming, Data Science, and scientific computing projects. He has published and presented papers on applied mathematics in Washington DC and New York, and also maintains a blog, DataScience Hacks (https://datasciencehacks.wordpress.com/). Currently, he is a graduate student in computational mathematics in New York. He loves exploring new problem solving techniques and software, from industrial mathematics to machine learning, in addition to reviewing Packt Publishing books.

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