Isabel Drost, Cofounder Apache Mahout. Mahout in Action is a hands-on introduction to machine learning with Apache Mahout. Following real-world examples, the book presents practical use cases and then illustrates how Mahout can be applied to solve them. Includes a free audio- and video-enhanced ebook. About the Technology. A computer system that learns and adapts as it collects data can be.
Meet Apache Mahout As you may have guessed from the title, this book is about putting a particular tool, Apache Mahout, to effective use in real life. It has three defining qualities. First, Mahout is an open source machine learning library from Apache. The algo-rithms it implements fall under the broad umbrella of machine learning or collective intelligence. This can mean many things, but at.
Introduction to Mahout The above video is the recorded session of the webinar conducted on 9th September’14. The topic of the webinar was “Introduction to Machine Learning with Mahout”.
Classification approaches in machine learning use stats to create models to classify documents. Therefore Machine learning is a very expansive and comprehensive concept and just how Apache Mahout helps out is given below. About Apache Mahout: Apache Mahout refers to an open source software project created by Apache Software foundation’s organization with the aim of coming up with machine.
Classification techniques decide how much a thing is or isn’t part of some type or category, or how much it does or doesn’t have some attribute. Classification, like clustering, is ubiquitous, but it’s even more behind the scenes. This paper exhibits the classification technique by using Mahout. The sample data was taken from 20.
Apache Mahout, a project developed by Apache Software Foundation, is meant for Machine Learning. It enables machines learn without being overtly programmed. It produces scalable machine learning algorithms, extracts recommendations and relationships from data sets in a simplified way. Apache Mahout is an open-source project, which is free to use under the Apache license. It runs on Hadoop.
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.
This book is a practical guide that explains the classification algorithms provided in Apache Mahout with the help of actual examples. Starting with the introduction of classification and model evaluation techniques, we will explore Apache Mahout and learn why it is a good choice for classification.