Author(s) Name: Kai Hwang, Min Chen
In this book, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. It is a definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies
Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples.
Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications.
Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools.
Table of Contents
1. Big Data Science and Machine Intelligence
2. Smart Clouds, Virtualization and Mashup Services
3. IoT Sensing, Mobile and Cognitive Systems
4. Supervised Machine Learning Algorithms
5. Unsupervised Machine Learning Algorithms
6. Deep Learning with Artificial Neural Networks
7. Machine Learning for Big Data in Healthcare Applications
8. Deep Reinforcement Learning and Social Media Analytics
ISBN: 9781119247029
Publisher: John Wiley & Sons
Year of Publication: 2017
Book Link: Home Page Url
