A Matrix Algebra Approach To Artificial Intelligence

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A Matrix Algebra Approach To Artificial Intelligence

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Author : Xian-Da Zhang
language : en
Publisher: Springer Nature
Release Date : 2020-05-23

A Matrix Algebra Approach To Artificial Intelligence written by Xian-Da Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-23 with Computers categories.

Matrix algebra plays an important role in many core artificial intelligence (AI) areas, including machine learning, neural networks, support vector machines (SVMs) and evolutionary computation. This book offers a comprehensive and in-depth discussion of matrix algebra theory and methods for these four core areas of AI, while also approaching AI from a theoretical matrix algebra perspective. The book consists of two parts: the first discusses the fundamentals of matrix algebra in detail, while the second focuses on the applications of matrix algebra approaches in AI. Highlighting matrix algebra in graph-based learning and embedding, network embedding, convolutional neural networks and Pareto optimization theory, and discussing recent topics and advances, the book offers a valuable resource for scientists, engineers, and graduate students in various disciplines, including, but not limited to, computer science, mathematics and engineering.

Mathematics For Machine Learning

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Author : Marc Peter Deisenroth
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-23

Mathematics For Machine Learning written by Marc Peter Deisenroth and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-23 with Computers categories.

Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

Introduction To Applied Linear Algebra

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Author : Stephen Boyd
language : en
Publisher: Cambridge University Press
Release Date : 2018-06-07

Introduction To Applied Linear Algebra written by Stephen Boyd and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-07 with Business & Economics categories.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Artificial Intelligence Enabled Businesses

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Author : Sweta Dixit
language : en
Publisher: John Wiley & Sons
Release Date : 2024-12-05

Artificial Intelligence Enabled Businesses written by Sweta Dixit 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 2024-12-05 with Business & Economics categories.

This book has a multidimensional perspective on AI solutions for business innovation and real-life case studies to achieve competitive advantage and drive growth in the evolving digital landscape. Artificial Intelligence-Enabled Businesses demonstrates how AI is a catalyst for change in business functional areas. Though still in the experimental phase, AI is instrumental in redefining the workforce, predicting consumer behavior, solving real-life marketing dynamics and modifications, recommending products and content, foreseeing demand, analyzing costs, strategizing, managing big data, enabling collaboration of cross-entities, and sparking new ethical, social and regulatory implications for business. Thus, AI can effectively guide the future of financial services, trading, mobile banking, last-mile delivery, logistics, and supply chain with a solution-oriented focus on discrete business problems. Furthermore, it is expected to educate leaders to act in an ever more accurate, complex, and sophisticated business environment with the combination of human and machine intelligence. The book offers effective, efficient, and strategically competent suggestions for handling new challenges and responsibilities and is aimed at leaders who wish to be more innovative. It covers the early stages of AI adoption by organizations across their functional areas and provides insightful guidance for practitioners in the suitable and timely adoption of AI. This book will greatly help to scale up AI by leveraging interdisciplinary collaboration with cross-functional, skill-diverse teams and result in a competitive advantage. Audience This book is for marketing professionals, organizational leaders, and researchers to leverage AI and new technologies across various business functions. It also fits the needs of academics, students, and trainers, providing insights, case studies, and practical strategies for driving growth in the rapidly evolving digital landscape.

System Design For Epidemics Using Machine Learning And Deep Learning

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Author : G. R. Kanagachidambaresan
language : en
Publisher: Springer Nature
Release Date : 2023-02-01

System Design For Epidemics Using Machine Learning And Deep Learning written by G. R. Kanagachidambaresan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Technology & Engineering categories.

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Math For Deep Learning

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Author : Ronald T. Kneusel
language : en
Publisher: No Starch Press
Release Date : 2021-11-23

Math For Deep Learning written by Ronald T. Kneusel and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Computers categories.

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network. In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.

Artificial Intelligence And Bioinformatics Applications For Omics And Multi Omics Studies

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Author : Angelo Facchiano
language : en
Publisher: Frontiers Media SA
Release Date : 2024-02-07

Artificial Intelligence And Bioinformatics Applications For Omics And Multi Omics Studies written by Angelo Facchiano and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-07 with Science categories.

Efficient Online Learning Algorithms For Total Least Square Problems

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Author : Xiangyu Kong
language : en
Publisher: Springer Nature
Release Date : 2024-07-17

Efficient Online Learning Algorithms For Total Least Square Problems written by Xiangyu Kong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-17 with Mathematics categories.

This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors’ latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided in this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors’ latest achievements or new methods around the practical industrial needs. In my opinion, this book can be assimilated by advanced undergraduates and graduate students, as well as statisticians, because of the new tools in data analysis, applied mathematics experts, because of the novel theories and techniques that we propose, engineers, above all for the applications in control, system identification, computer vision, and signal processing.

Machine Learning And Big Data Analytics

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Author : Rajiv Misra
language : en
Publisher: Springer Nature
Release Date : 2023-06-06

Machine Learning And Big Data Analytics written by Rajiv Misra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Mathematics categories.

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

Artificial Intelligence For Cardiovascular Disease

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Author : Rishabha Malviya
language : en
Publisher: CRC Press
Release Date : 2025-04-04

Artificial Intelligence For Cardiovascular Disease written by Rishabha Malviya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-04 with Computers categories.

“A ground-breaking compilation that focuses on the integration of artificial intelligence and machine learning applications in cardiovascular healthcare... Offers helpful insights into the enormous potential of AI to change the landscape of cardiovascular care, from basic AI concepts to the most recent developments in AI-assisted wearables and diagnostic imaging.” —From the Foreword by Dr. Dhruv Galgotia, CEO–Galgotias University, India Today, the need for effective and cutting-edge methods of diagnosis, treatment, and prevention of cardiovascular diseases is greater than ever before. Integrating deep learning and artificial intelligence into digital healthcare and medical environments has the potential to revolutionize cardiovascular health. The new book addresses this need by discussing emerging uses of artificial intelligence and machine learning in the prediction, diagnosis, treatment, and management of cardiovascular diseases. It looks at AI in wearable technology, nuclear cardiac imaging, coronary CT angiography, and non-contrast cardiac CT methods. It also explores the application of machine learning techniques in predicting and diagnosing cardiovascular diseases, revealing the potential for data-driven predictions and decisions that can improve patient outcomes. It explores the potential of AI in a variety of cardiology applications, including the classification of ECG signals, wearables with AI support, speech technologies in clinical settings, and more.