Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python – PDF

Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python – PDF

“Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python” serves as an essential guide to the foundational concepts of data analysis, cognitive science, and computational intelligence, encompassing artificial intelligence and machine learning. The ebook emphasizes core ideas, methodologies, and tools in computational intelligence that can be leveraged across various data analysis techniques, including mathematical programming, evolutionary simulation, machine learning, and logic-based models.

Readers will delve into both theoretical and practical dimensions of cognitive science and data analysis, examining data analytics through the lenses of description, evolution, and real-world applicability. The authors trace the historical development of cognitive analytics, addressing methodological issues in philosophy, syntax, semantics, and the comprehension of generative linguistics, memory theory, and processing frameworks. They also explore both structured and unstructured data, as well as qualitative and quantitative measures—covering nominal, ordinal, interval, and ratio scales.

This ebook Cognitive Science, Computational Intelligence, and Data Analytics is meticulously designed to meet readers’ needs in terms of both type and foundational knowledge, including comprehensive discussions on multivariate analysis, CRISP methodology, and SEMMA methodology. Each chapter is infused with practical, hands-on learning experiences, featuring real-world applications, case studies, and Python programs that correspond to the key concepts presented, ensuring readers can apply their knowledge effectively.

– Demystifies the theory of data analytics using a step-by-step approach

– Introduces foundational data analytics techniques such as CRISP-DM, SEMMA, and Object Detection Models in the context of computational intelligence methods and tools

– Covers key concepts of multivariate and cognitive data analytics such as factor analytics, principal component analytics, linear regression analysis, logistic regression analysis, and value chain applications

– Covers the intersection of cognitive science, computational intelligence, and data analytics by providing examples and case studies with applied algorithms, mathematics, and Python programming code

978-0443160790, 978-0443160783

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