Cognitive computing and deep learning

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 t

This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy is

A comprehensive guide to learning technologies that unlock the value in big dataCognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and der

Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday de

How deep learning -- from Google Translate to driverless cars to personal cognitive assistants -- is changing our lives and transforming every sector of the economy.The deep learning revolution has br

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex p

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.Key FeaturesExplore machine learning techniques with prominent ope

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database m

Deep learning is a committed approach to learning. It is a process of constructing and interpreting new knowledge in light of prior cognitive structures and experiences, which can be applied in new, u

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that

This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece,

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deplo

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fail

This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical,