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Learning Algorithms For Tracking Changing Concepts And An Investigation Into The Error Surfaces Of Single Artificial Neurons
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Book Synopsis Learning Algorithms for Tracking Changing Concepts and an Investigation Into the Error Surfaces of Single Artificial Neurons by : Mark Herbster
Download or read book Learning Algorithms for Tracking Changing Concepts and an Investigation Into the Error Surfaces of Single Artificial Neurons written by Mark Herbster and published by . This book was released on 1998 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis American Doctoral Dissertations by :
Download or read book American Doctoral Dissertations written by and published by . This book was released on 1998 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2000 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multivariate Statistical Machine Learning Methods for Genomic Prediction by : Osval Antonio Montesinos López
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1522507892 Total Pages :1810 pages Book Rating :4.5/5 (225 download)
Book Synopsis Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-07-26 with total page 1810 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.
Download or read book Perceptrons written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-25 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Perceptrons The perceptron is a technique for supervised learning of binary classifiers that is used in the field of machine learning. A function known as a binary classifier is one that can determine whether or not an input, which is often portrayed by a vector of numbers, is a member of a particular category. It is a kind of linear classifier, which means that it is a classification method that forms its predictions on the basis of a linear predictor function by combining a set of weights with the feature vector. In other words, it creates its predictions based on a linear predictor function. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Perceptron Chapter 2: Supervised learning Chapter 3: Support vector machine Chapter 4: Linear classifier Chapter 5: Pattern recognition Chapter 6: Artificial neuron Chapter 7: Hopfield network Chapter 8: Backpropagation Chapter 9: Feedforward neural network Chapter 10: Multilayer perceptron (II) Answering the public top questions about perceptrons. (III) Real world examples for the usage of perceptrons in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of perceptrons. What Is Artificial Intelligence Series The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Book Synopsis Neural Network Design by : Martin T. Hagan
Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deterministic Artificial Intelligence by : Timothy Sands
Download or read book Deterministic Artificial Intelligence written by Timothy Sands and published by BoD – Books on Demand. This book was released on 2020-05-27 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book.
Book Synopsis Canadian Geotechnical Journal by : National Research Council Canada
Download or read book Canadian Geotechnical Journal written by National Research Council Canada and published by . This book was released on 2003 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of Machine Learning by : Prashant Johri
Download or read book Applications of Machine Learning written by Prashant Johri and published by Springer Nature. This book was released on 2020-05-04 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
Book Synopsis Fundamentals of Deep Learning by : Nikhil Buduma
Download or read book Fundamentals of Deep Learning written by Nikhil Buduma and published by "O'Reilly Media, Inc.". This book was released on 2017-05-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning
Book Synopsis Neural Network Training Algorithms Based on Quadratic Error Surface Models by : Sayandev Mukherjee
Download or read book Neural Network Training Algorithms Based on Quadratic Error Surface Models written by Sayandev Mukherjee and published by . This book was released on 1997 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Evolutionary Learning Algorithms for Neural Adaptive Control by : Dimitris C. Dracopoulos
Download or read book Evolutionary Learning Algorithms for Neural Adaptive Control written by Dimitris C. Dracopoulos and published by Springer. This book was released on 1997-08-15 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: After an introduction to neural networks and genetic algorithms, this volume describes in detail how neural networks and evolutionary techniques (specifically genetic algorithms and genetic programming) can be applied to the adaptive control of complex dynamic systems (including chaotic ones). A number of examples are presented and useful tips are given for the application of the techniques described. The fundamentals of dynamic systems theory and classical adaptive control are also given. This volume will be of particular interest to undergraduate and postgraduate students taking courses in neural networks, genetic algorithms or control systems, researchers in neural networks and genetic algorithms who need to extend their field of application to dynamic systems and control, and control theorists/professionals who would like to use these advanced learning techniques for solving high-nonlinear control theory problems.
Download or read book Applied Mechanics Reviews written by and published by . This book was released on 1992 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Book Synopsis The Deep Learning Revolution by : Terrence J. Sejnowski
Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr
Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
