Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model
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Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model
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Author : Waymond Rodgers
language : en
Publisher: Bentham Science Publishers
Release Date : 2022-07-20
Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model written by Waymond Rodgers and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Computers categories.
This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.
Artificial Intelligence In A Throughput Model
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Author : Taylor & Francis Group
language : en
Publisher: CRC Press
Release Date : 2021-09
Artificial Intelligence In A Throughput Model written by Taylor & Francis Group and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09 with categories.
Physical and behavioral biometric technologies such as fingerprinting, facial recognition, voice identification, etc. have enhanced the level of security substantially in recent years. Governments and corporates have employed these technologies to achieve better customer satisfaction. However, biometrics faces major challenges in reducing criminal, terrorist activities and electronic frauds, especially in choosing appropriate decision-making algorithms. To face this challenge, new developments have been made, that amalgamate biometrics with artificial intelligence (AI) in decision-making modeling. Advanced software algorithms of AI, processing information offered by biometric technology, achieve better results. This has led to growth in the biometrics technology industry, and is set to increase the security and internal control operations manifold. This book provides an overview of the existing biometric technologies, decision-making algorithms and the growth opportunity in biometrics. The book proposes a throughput model, which draws on computer science, economics and psychology to model perceptual, informational sources, judgmental processes and decision choice algorithms. It reviews how biometrics might be applied to reduce risks to individuals and organizations, especially when dealing with digital-based media.
From Natural To Artificial Intelligence
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Author : Ricardo López-Ruiz
language : en
Publisher:
Release Date : 2018
From Natural To Artificial Intelligence written by Ricardo López-Ruiz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Algorithms categories.
An Introduction To Machine Learning
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Author : Gopinath Rebala
language : en
Publisher: Springer
Release Date : 2019-05-07
An Introduction To Machine Learning written by Gopinath Rebala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-07 with Technology & Engineering categories.
Just like electricity, Machine Learning will revolutionize our life in many ways – some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; Not tied to any specific software language or hardware implementation.
Artificial Intelligence In Practice
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Author : Bernard Marr
language : en
Publisher: John Wiley & Sons
Release Date : 2019-05-28
Artificial Intelligence In Practice written by Bernard Marr and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-28 with Business & Economics categories.
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
Genetic Algorithms In Search Optimization And Machine Learning
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Author : David Edward Goldberg
language : en
Publisher: Addison-Wesley Professional
Release Date : 1989
Genetic Algorithms In Search Optimization And Machine Learning written by David Edward Goldberg and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Algorithms categories.
A gentle introduction to genetic algorithms. Genetic algorithms revisited: mathematical foundations. Computer implementation of a genetic algorithm. Some applications of genetic algorithms. Advanced operators and techniques in genetic search. Introduction to genetics-based machine learning. Applications of genetics-based machine learning. A look back, a glance ahead. A review of combinatorics and elementary probability. Pascal with random number generation for fortran, basic, and cobol programmers. A simple genetic algorithm (SGA) in pascal. A simple classifier system(SCS) in pascal. Partition coefficient transforms for problem-coding analysis.
Multi Objective Optimization Using Artificial Intelligence Techniques
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Author : Seyedali Mirjalili
language : en
Publisher: Springer
Release Date : 2019-07-24
Multi Objective Optimization Using Artificial Intelligence Techniques written by Seyedali Mirjalili and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Technology & Engineering categories.
This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Braunwald S Heart Disease E Book
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Author : Peter Libby
language : en
Publisher: Elsevier Health Sciences
Release Date : 2021-10-15
Braunwald S Heart Disease E Book written by Peter Libby and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-15 with Medical categories.
Current, comprehensive, and evidence-based Braunwald’s Heart Disease remains the most trusted reference in the field and the leading source of reliable cardiology information for practitioners and trainees worldwide. The fully updated 12th Edition continues the tradition of excellence with dependable, state-of-the-art coverage of new drugs, new guidelines, more powerful imaging modalities, and recent developments in precision medicine that continue to change and advance the practice of cardiovascular medicine. Written and edited by global experts in the field, this award-winning text is an unparalleled multimedia reference for every aspect of this complex and fast-changing area. Offers balanced, dependable content on rapidly changing clinical science, clinical and translational research, and evidence-based medicine. Includes 76 new contributing authors and 14 new chapters that cover Artificial intelligence in Cardiovascular Medicine; Wearables; Influenza, Pandemics, COVID-19, and Cardiovascular Disease; Tobacco and Nicotine Products in Cardiovascular Disease; Cardiac Amyloidosis; Impact of the Environment on Cardiovascular Health, and more. Features a new introductory chapter Cardiovascular Disease: Past, Present, and Future by Eugene Braunwald, MD, offering his unique, visionary approach to the field of cardiology. Dr. Braunwald also curates the extensive, bimonthly online updates that include "Hot Off the Press" (with links to Practice Update) and "Late-Breaking Clinical Trials". Provides cutting-edge coverage of key topics such as proteomics and metabolomics, TAVR, diabetocardiology, and cardio-oncology. Contains 1,850 high-quality illustrations, radiographic images, algorithms, and charts, and provides access to 215 videos called out with icons in the print version. Highlights the latest AHA, ACC, and ESC guidelines to clearly summarize diagnostic criteria and clinical implications. Provides tightly edited, focused content for quick, dependable reference. Flexible format options include either one or two volumes in print, as well as a searchable eBook with ongoing updates.
Evaluating The Effectiveness Of Artificial Intelligence Systems In Intelligence Analysis
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Author : Daniel Ish
language : en
Publisher:
Release Date : 2021
Evaluating The Effectiveness Of Artificial Intelligence Systems In Intelligence Analysis written by Daniel Ish and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.
The authors develop methods for assessing the impact of deploying artificial intelligence (AI) systems to support intelligence missions.
Hands On Machine Learning With R
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Author : Brad Boehmke
language : en
Publisher: CRC Press
Release Date : 2019-11-07
Hands On Machine Learning With R written by Brad Boehmke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Business & Economics categories.
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.