Apache Mahout Essentials

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Apache Mahout Essentials by Jayani Withanawasam

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Apache Mahout is a scalable machine learning library that provides algorithms for classification, clustering, and recommendations.

This book helps you to use Apache Mahout to implement widely used machine learning algorithms in order to gain better insights about large and complex datasets in a scalable manner.

Starting from fundamental concepts in machine learning and Apache Mahout, real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each machine learning technique. Further, this book contains a complete step-by-step guide to set up Apache Mahout in the production environment, using Apache Hadoop to unleash the scalable power of Apache Mahout in a distributed environment. Finally, you are guided toward the data visualization techniques for Apache Mahout, which make your data come alive!

Who this book is for

If you are a Java developer or a data scientist who has not worked with Apache Mahout previously and want to get up to speed on implementing machine learning on big data, then this is a concise and fast-paced guide for you.



  • CC BY-NC-SA 3.0 PH
  • The author's reference is not required

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