Cloud Computing for Machine Learning and Cognitive Applications (Hardcover)

Kai Hwang

ISBN 10: 026203641X / ISBN 13: 9780262036412

Edité par MIT Press Ltd, Cambridge, Mass., 2017

A propos de cet article

Hardcover. The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies.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. The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

N° de réf. du vendeur 9780262036412

Détails bibliographiques

• Titre: Cloud Computing for Machine Learning and Cognitive Applications (Hardcover)
• Éditeur: MIT Press Ltd, Cambridge, Mass.
• Date de parution: 2017
• Langue: anglais
• ISBN à 10 chiffres: 026203641X
• ISBN à 13 chiffres: 9780262036412
• Reliure: Hardcover
• État de l'article: new

A propos de ce titre

Synopsis

The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies.

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.

À propos de l?auteur

Kai Hwang is a Professor of Electrical Engineering and Computer Science at the University of Southern California (USC). Cloud and Cognitive Computing is based on his Cloud Computing course.