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Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

. Bringing together machine learning, cognitive science and other aspects of artificial intelligence to help provide a roadmap for future research on;

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Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have;

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Machine Learning and Cognitive Science Applications in Cyber Security

In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a;

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Cybernetics Cognition and Machine Learning Applications

This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning;

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Statistical Reinforcement Learning

field, Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms;

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Statistical Reinforcement Learning

model-free approaches, policy iteration, and policy search methods. Covers the range of reinforcement learning algorithms from a modern;

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Cognitive Informatics, Computer Modelling, and Cognitive Science

in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation;

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Cybernetics Cognition and Machine Learning Applications

of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and;

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Learning in Humans and Machines

The book discusses the analysis, comparison and integration of computational approaches to learning and research on human learning;

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Fundamentals of Machine Learning

Interest in machine learning is exploding worldwide, both in research and for industrial applications. Machine learning is fast becoming a;

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Algorithmic Aspects of Machine Learning

be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method;

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Algorithmic Aspects of Machine Learning

be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method;

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Representation Learning

) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained;

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Representation Learning

) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained;

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Cognitive Computing Recipes

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

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User Interface Inspection Methods

is the pluralistic walkthrough, in which a user is invited to provide feedback while members of a product team listen, observe the user, and ask;

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Advances in Cybernetics Cognition and Machine Learning for Communication Techn

This book highlights recent advances in Cybernetics, Machine Learning and Cognitive Science applied to Communications Engineering and;

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Practical Machine Learning

Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive;

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Machine Learning and Cognition in Enterprises

Learn about the emergence and evolution of IT in the enterprise, see how machine learning is transforming business intelligence, and;

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Machine Learning for Biometrics

, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this;

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Lie Group Machine Learning

and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine;

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Statistical and Machine Learning Approaches for Network Analysis

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning * Features a companion website with an;

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Optimization for Machine Learning

communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science;

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Data Science in Practice

This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We;

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Applications of Machine Learning in Wireless Communications

. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where;

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Metaheuristics in Machine Learning

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered;

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