Apache Mahout Essentials: Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout

✍ Scribed by Jayani Withanawasam

• Publisher: Packt Publishing
• Year: 2015
• Tongue: English
• Leaves: 165
• Category: Library

✦ Synopsis

Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably. This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains complicated but very effective machine learning algorithms simply, in relation to real-world practical examples. Starting from the fundamental concepts of machine learning and Apache Mahout, this book guides you through Apache Mahout's implementations of machine learning techniques including classification, clustering, and recommendations. During this exciting walkthrough, real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each technique. Finally, you will learn vdata visualization techniques for Apache Mahout to bring your data to life.