Cloud Computing for Machine Learning and Cognitive Applications
Kai Hwang
Sold by Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
AbeBooks Seller since April 17, 2013
New - Hardcover
Condition: New
Quantity: 2 available
Add to basketSold by Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
AbeBooks Seller since April 17, 2013
Condition: New
Quantity: 2 available
Add to basketThis is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Seller Inventory # ABNR-208889
This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data.
This textbook is designed to train college students to master modern cloud computing systems in operating principles, architecture design, machine learning algorithms, programming models and software tools for big data mining, analytics, and cognitive applications. The book will be suitable for use in one-semester computer science or electrical engineering courses on cloud computing, machine learning, cloud programming, cognitive computing, or big data science. The book will also be very useful as a reference for professionals who want to work in cloud computing and data science.
Cloud and Cognitive Computing begins with two introductory chapters on fundamentals of cloud computing, data science, and adaptive computing that lay the foundation for the rest of the book. Subsequent chapters cover topics including cloud architecture, mashup services, virtual machines, Docker containers, mobile clouds, IoT and AI, inter-cloud mashups, and cloud performance and benchmarks, with a focus on Google's Brain Project, DeepMind, and X-Lab programs, IBKai HwangM SyNapse, Bluemix programs, cognitive initiatives, and neurocomputers. The book then covers machine learning algorithms and cloud programming software tools and application development, applying the tools in machine learning, social media, deep learning, and cognitive applications. All cloud systems are illustrated with big data and cognitive application examples.
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