Deep Learning For Cognitive Computing Systems
Download Deep Learning For Cognitive Computing Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Learning For Cognitive Computing Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Deep Learning for Cognitive Computing Systems
Author: M.G. Sumithra
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2022-12-31
Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.
Cloud Computing for Machine Learning and Cognitive Applications
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.
Cognitive Computing Systems
This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures. Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more. With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.