TINKU ACHARYA, PHD, Senior Executive vice president and Chief Science Officer of Avisere Inc., Tucson, Arizona, is involved in multimedia data mining applications. He is also an adjunct professor in the Department of Electrical Engineering at Arizona State University. He was recognized as the Most Prolific Inventor of Intel Corporation Worldwide in 1999.
There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph data, the Web page for the book should be http://www.eecs.wsu.edu/MGD.
Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book:Examines cloud computing, data analytics, and sustainability and how they relate to IoT overs the scope of consumer, government, and enterprise applications Includes best practices, business model, and real-world case studies Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences. Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015).
"Dr. Ahamed is correct in observing that 'silicon and glass have altered the rhythm of mind' and that computers need to be more 'human.'"
—Bishnu S. Atal, Member, National Academy of Engineering
This book combines philosophical, societal, and artificial intelligence concepts with those of computer science and information technology to demonstrate novel ways in which computers can simplify data mining on the Internet. It describes numerous innovative methods that go well beyond information retrieval to allow computers to accomplish such tasks as processing, classifying, prioritizing, and reconstituting knowledge.
The book is divided into five parts:
New knowledge sensing and filtering environments
Concept building and wisdom machines
General structure and theory of knowledge
Verb functions and noun objects
Humanistic and semi-human systems
This book offers new mathematical methodologies and concrete HW/SW/FW configurations for the IT specialist to help their corporations explore, exploit, compete, and win global market share.
Key features:Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors’ own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book.
The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.
The problem with the reference books is that they are too descriptive for last moment studies. Whereas the problem with local publications is that they are inaccurate as compared to the reference books.
This particular book encapsulates the subject notes on Data Mining & Business Intelligence with the combined benefits of reference books & local publications. It has the accuracy of a reference book as well as the abstraction of a local publication.
The author studied the subject from various sources such as web lectures, reference books, online tutorials & so on. After having a thorough understanding of the subject, the author compiled this book for an easy understanding of the subject.
This book presents the content in the form of question & answers, with utmost simplicity of language, and in an abstract manner so that it can be used for last moment studies. This book can be used by:
Ø Students to prepare for their examinations
Ø Professionals to prepare for job interviews.
Ø Individuals willing to have a basic understanding of the domain: Data Mining & Business Intelligence.