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Computational Statistical Methodologies and Modeling for Artificial Intelligence

2023-03-31 Computers
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Release : 2023-03-31
Genre : Computers
Kind : eBook
Book Rating : 094/5 ( reviews)

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Book Synopsis Computational Statistical Methodologies and Modeling for Artificial Intelligence by : Priyanka Harjule

Download or read book Computational Statistical Methodologies and Modeling for Artificial Intelligence written by Priyanka Harjule. This book was released on 2023-03-31. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Computational Statistical Methodologies and Modeling for Artificial Intelligence

2023-03-31 Computers
Download Computational Statistical Methodologies and Modeling for Artificial Intelligence PDF Online Free

Author :
Release : 2023-03-31
Genre : Computers
Kind : eBook
Book Rating : 078/5 ( reviews)

GET EBOOK


Book Synopsis Computational Statistical Methodologies and Modeling for Artificial Intelligence by : Priyanka Harjule

Download or read book Computational Statistical Methodologies and Modeling for Artificial Intelligence written by Priyanka Harjule. This book was released on 2023-03-31. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Computational and Statistical Methods in Intelligent Systems

2018-08-29 Technology & Engineering
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Release : 2018-08-29
Genre : Technology & Engineering
Kind : eBook
Book Rating : 11X/5 ( reviews)

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Book Synopsis Computational and Statistical Methods in Intelligent Systems by : Radek Silhavy

Download or read book Computational and Statistical Methods in Intelligent Systems written by Radek Silhavy. This book was released on 2018-08-29. Available in PDF, EPUB and Kindle. Book excerpt: This book presents real-world problems and pioneering research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of intelligent systems. It gathers the peer-reviewed proceedings of the 2nd Computational Methods in Systems and Software 2018 (CoMeSySo 2018), a conference that broke down traditional barriers by being held online. The goal of the event was to provide an international forum for discussing the latest high-quality research results.

Handbook of Computational Social Science, Volume 2

2021-11-10 Computers
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Release : 2021-11-10
Genre : Computers
Kind : eBook
Book Rating : 592/5 ( reviews)

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Book Synopsis Handbook of Computational Social Science, Volume 2 by : Uwe Engel

Download or read book Handbook of Computational Social Science, Volume 2 written by Uwe Engel. This book was released on 2021-11-10. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors.

Computationally Intensive Statistics for Intelligent IoT

2021-10-02 Technology & Engineering
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Release : 2021-10-02
Genre : Technology & Engineering
Kind : eBook
Book Rating : 362/5 ( reviews)

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Book Synopsis Computationally Intensive Statistics for Intelligent IoT by : Debabrata Samanta

Download or read book Computationally Intensive Statistics for Intelligent IoT written by Debabrata Samanta. This book was released on 2021-10-02. Available in PDF, EPUB and Kindle. Book excerpt: The book covers computational statistics, its methodologies and applications for IoT device. It includes the details in the areas of computational arithmetic and its influence on computational statistics, numerical algorithms in statistical application software, basics of computer systems, statistical techniques, linear algebra and its role in optimization techniques, evolution of optimization techniques, optimal utilization of computer resources, and statistical graphics role in data analysis. It also explores computational inferencing and computer model's role in design of experiments, Bayesian analysis, survival analysis and data mining in computational statistics.

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