Australasia's Biggest Online Store

We won't be beaten by anyone. Guaranteed

Machine Learning Models and Algorithms for Big Data Classification
By

Rating
This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.
Product Details

Table of Contents

Science of Information.- Part I Understanding Big Data.- Big Data Essentials.- Big Data Analytics.- Part II Understanding Big Data Systems.- Distributed File System.- MapReduce Programming Platform.- Part III Understanding Machine Learning.- Modeling and Algorithms.- Supervised Learning Models.- Supervised Learning Algorithms.- Support Vector Machine.- Decision Tree Learning.- Part IV Understanding Scaling-Up Machine Learning.- Random Forest Learning.- Deep Learning Models.- Chandelier Decision Tree.- Dimensionality Reduction.

About the Author

Shan Suthaharan is a Professor of Computer Science at the University of North Carolina at Greensboro (UNCG), North Carolina, USA. He also serves as the Director of Undergraduate Studies at the Department of Computer Science at UNCG. He has more than twenty-five years of university teaching and administrative experience, and has taught both undergraduate and graduate courses. His aspiration is to educate and train students so that they can prosper in the computer field by understanding current real-world and complex problems, and develop efficient techniques and technologies. His current teaching interests include big data analytics and machine learning, cryptography and network security, and computer networking and analysis. He earned his doctorate in Computer Science from Monash University, Australia. Since then, he has been actively working on disseminating his knowledge and experience through teaching, advising, seminars, research, and publications. Dr. Suthaharan enjoys investigating real-world, complex problems, and developing and implementing algorithms to solve those problems using modern technologies. The main theme of his current research is the signature discovery and event detection for a secure and reliable environment. The ultimate goal of his research is to build a secure and reliable environment using modern and emerging technologies. His current research primarily focuses on the characterization and detection of environmental events, the exploration of machine learning techniques, and the development of advanced statistical and computational techniques to discover key signatures and detect emerging events from structured and unstructured big data. Dr. Suthaharan has authored or co-authored more than seventy-five research papers in the areas of computer science, and published them in international journals and referred conference proceedings. He also invented a key management and encryption technology, which has been patented in Australia, Japan, and Singapore. He also received visiting scholar awards from and served as a visiting researcher at the University of Sydney, Australia; the University of Melbourne, Australia; and the University of California, Berkeley, USA. He was a senior member of the Institute of Electrical and Electronics Engineers, and volunteered as an elected chair of the Central North Carolina Section twice. He is a member of Sigma Xi, the Scientific Research Society, and a Fellow of the Institution of Engineering and Technology.

Reviews

"This book is a good introduction to machine learning models for big data classification ... . Typical of a Springer book, this one is concise, clear, and well organized. ... each chapter contains programming examples and references ... . this book is useful if you want to know more about machine learning models and algorithms for big data classification." (J. Myerson, Computing Reviews, February, 2016)

How Fishpond Works
Fishpond works with suppliers all over the world to bring you a huge selection of products, really great prices, and delivery included on over 25 million products that we sell. We do our best every day to make Fishpond an awesome place for customers to shop and get what they want — all at the best prices online.
Webmasters, Bloggers & Website Owners
You can earn a 5% commission by selling Machine Learning Models and Algorithms for Big Data Classification: Thinking with Examples for Effective Learning: 2016 (Integrated Series in Information Systems) on your website. It's easy to get started - we will give you example code. After you're set-up, your website can earn you money while you work, play or even sleep! You should start right now!
Authors / Publishers
Are you the Author or Publisher of a book? Or the manufacturer of one of the millions of products that we sell. You can improve sales and grow your revenue by submitting additional information on this title. The better the information we have about a product, the more we will sell!
Item ships from and is sold by Fishpond World Ltd.
Back to top