CreateSpace, 2016. — 222 p. A gentle journey through the mathematics of neural networks, and making your own using the Python computer language. Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun...
Berlin/Boston: De Gruyter, 2018. — 296 p. — ISBN: 3110449625. The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential...
СПб.: Питер, 2024. — 224 с. — (IT для бизнеса). — ISBN: 978-5-44-612232-5. Уже сейчас нейросети выполняют тысячи контент-задач в разных сферах. От слоганов, статей и постов до учебных программ, выступлений и подбора креативных идей. Умение грамотно «общаться» с ИИ все чаще становится серьезным и порой даже главным карьерным или личным бонусом. Именно развитию навыков работы с...
Springer International Publishing AG, 2017. — 457 p. — (Texts in Applied Mathematics 66) — ISBN10: 331951170X. This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction...
Princeton University Press, 2021. — 368 p. — ISBN 978-0691181226. What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The...
Bentham Science Publishers, 2015. — ISBN: 978-1681080918. An intelligent system is one which exhibits characteristics including, but not limited to, learning, adaptation, and problem-solving. Artificial Neural Network (ANN) Systems are intelligent systems designed on the basis of statistical models of learning that mimic biological systems such as the human central nervous...
Blue Windmill Media, 2017. — 248 p. Neural networks have made a gigantic comeback in the last few decades and you likely make use of them everyday without realizing it, but what exactly is a neural network? What is it used for and how does it fit within the broader arena of machine learning? On a high level, a network learns just like we do, through trial and error. This is...
CreateSpace Independent Publishing, 2018. — 114 p. — ISBN: 171759445X. Are you looking to get a better understanding of neural networks and their applications? Neural networks are used to model complex patterns for prediction and simulation. It uses the processing pattern used by brain neurons to achieve this. Neural Networks are good at processing complex , non-linear...
Springer, 2022. — 528 p. — ISBN 978-3-030-92525-3. This book focuses on neuromorphic computing principles and organization and how to build fault-tolerant scalable hardware for large and medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how to design a spike-based neuromorphic system to...
Packt Publishing, 2018. — 218 p. — ISBN: 978-1-78839-230-3. Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision...
Packt Publishing, 2023. — 196 p. — ISBN 978-1804617625. Neuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks. This book provides an overview of AI and its inner mechanics, covering both symbolic and neural network approaches. You'll begin by...
Amazon Digital Services LLC, 2018. — 128 p. — ASIN B07GF5KP9R This book is an introduction to Intent Based Networking and how your business can leverage many of the benefits that it realises through network modernisation, optimisation and business alignment. Organisations around the world of all sizes are having to adjust to doing business globally. But one of the biggest...
Packt Publishing, 2017. — 288 p. — ISBN10: 1788397878, 13 978-1788397872. True EPUB Uncover the power of artificial neural networks by implementing them through R code.
2nd Edition. — Apress Media LLC, 2022. — 640 p. — ISBN-13 (electronic): 978-1-4842-7368-5. Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps...
Packt, 2019. - 462p. - ISBN: 9781789536089 Book Description Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features Design and create neural network architectures on different domains using Keras Integrate neural network models in your applications using this highly practical guide Get ready for the future of neural...
Prentice-Hall, 2017. — 572 p. — ISBN13: 978-8120353343. This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as...
3rd edition. — Humana Press, 2021. — 368 p. — ISBN 978-1-0716-0825-8. This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover a wide variety of topics, including the analysis of intracellular sorting information, prediction of the behavior of bacterial communities, biometric authentication,...
Packt Publishing, 2017. — 270 p. — ASIN B0748NMHYL. Key Features Develop a strong background in neural networks with R, to implement them in your applications Learn how to build and train neural network models to solve complex problems Implement solutions from scratch Covering real-world case studies to illustrate the power of neural network models Book Description Neural...
Springer, 2018. — 245 p. — ISBN: 978-9811301995. This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting...
Apress, 2018. — 139 p. — ISBN13: 9781484235065. Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. There are no prerequisites here and you won't see a single line of computer code in this book....
Springer International Publishing AG, 2017. — 90 p. — ISBN: 978-3-319-67770-5. The authors discuss in the first part of this book, the semantic aspects of spatio-temporal graph data in two application domains, viz., urban transportation and social networks. Then the authors present representational models and data structures, which can effectively capture these semantics, while...
Apress, 2019. — 640 p. — ISBN13: (electronic): 978-1-4842-4421-0. Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of...
Wiley, 2023. —– 243 p. — ISBN 9781119901990. Systems Engineering Neural Networks a complete and authoritative discussion of systems engineering and neural networks. In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems...
CRC Press, 2020. — 248 p. — ISBN: 9781138364509. Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It...
De Gruyter, 2022. — 154 p. — ISBN 978-3-11-065641-1. Neural Networks is an integral part in machine learning and a known tool for controlling nonlinear processes. The area is under rapid development and provides a tool for modelling and controlling of advanced processes. This book provides a comprehensive overview for modelling, simulation, measurement and control strategies...
Packt Publishing, 2017. — 270 p. — ISBN: 978-1-78712-605-3. Create and unleash the power of neural networks by implementing professional Java code About This Book Learn to build amazing projects using neural networks including forecasting the weather and pattern recognition Explore the Java multi-platform feature to run your personal neural networks everywhere This step-by-step...
CRC Press, 2022. — 412 p. — ISBN 9781003307822. The text discusses recurrent neural networks for prediction and offers new insights into the learning algorithms, architectures, and stability of recurrent neural networks. It discusses important topics including recurrent and folding networks, long short-term memory (LSTM) networks, gated recurrent unit neural networks, language...
Apress Media, LLC., 2023. — 223 p. — ISBN-13: 978-1-4842-8998-3. Demystify the creation of efficient AI systems using the model-based reinforcement learning Unity ML-Agents - a powerful bridge between the world of Unity and Python. We will start with an introduction to the field of AI, then discuss the progression of AI and where we are today. We will follow this up with a...
EHGBooks, 2018. — 397 p. — ASIN B07FHYXDYG. This book provides frequently studied and used machines together with soft computing methods such as evolutionary computation. The main topics of the machine learning cover Artificial Neural Networks (ANNs), Radial Basis Function Networks (RBFNs), Fuzzy Neural Networks (FNNs), Support Vector Machines (SVMs), and Wilcoxon Learning...
Springer, 2022. — 358 p. — ISBN 978-3-030-83814-0. Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to...
Springer, 2020. — 241 p. — ISBN 978-3-030-37223-1. Introduces in one volume all the trends that can be used to overcome Moore’s law limitations. Describes in detail Neuromorphic, Approximate, Parallel, In Memory, and Quantum Computing concepts, in a manner accessible to a wide variety of readers. Compares tradeoffs between the various paradigms discussed. An Introduction: New...
Academic Press, 2019. — 324 p. — ISBN 978-0-12-815254-6. Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black...
Springer, 2021. — 197 p. — ISBN 978-3-030-75648-2. The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially...
Springer, 2021. — 233 p. — (Lecture Notes on Numerical Methods in Engineering and Sciences). — ISBN 978-3030661106. This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of...
De Gruyter, 2022. — 174 p. — (De Gruyter Series in Applied and Numerical Mathematics 06). — 978-3-11-078318-6. Нейронные сети и численный анализ Artificial Intelligence, Deep Learning, Machine Learning - whatever you’re doing if you don’t understand it - learn it. Because otherwise you’re going to be a dinosaur within 3 years. This book uses numerical analysis as the main tool...
Springer, 2018. — 544 p. — (Smart Innovation, Systems and Technologies). — ISBN10: 3319950975, 13 978-3319950976. This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors,...
Academic Press, 2016. — 484 p. — ISBN 978-0-12-801560-5. Studying brain networks has become a truly interdisciplinary endeavor, attracting students and seasoned researchers alike from a wide variety of academic backgrounds. What has been lacking is an introductory textbook that brings together the different fields and provides a gentle introduction to the major concepts and...
Springer, 2020. — 315 p. — (Advances in Computer Vision and Pattern Recognition). — ISBN: 978-3-030-42128-1 (eBook). Современный Подход для Компьютерного Видения, используя Основанные на графе Методы и Глубокие Нейронные сети. This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive...
Leanpub, Eric Ma and Mridul Seth, 2021. – 191 p. Сетевой анализ стал проще: введение в сетевой анализ и прикладную теорию графов с использованием Python и NetworkX Are you interested in learning about graph theory and applied network analysis, leveraging your Python skills? Then this is the book for you! See how network science & graph theory connects with a variety of data...
Springer, 2022. — 211 p. — eBook ISBN 978-3-658-40004-0. Artificial intelligence (AI) is a concept, whose meaning and perception has changed considerably over the last decades. Starting off with individual and purely theoretical research efforts in the 1950s, AI has grown into a fully developed research field of modern times and may arguably emerge as one of the most important...
Packt Publishing, 2016. — 244 p. — ISBN: 978-1-78588-090-2. Код примеров к книге выложен здесь. Unleash the power of neural networks by implementing professional Java code. Vast quantities of data are produced every second. In this context, neural networks become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data. One of the...
O’Reilly Media, 2019. — 228 p. — ISBN: 978-1-492-04495-6. As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately “fool” them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process...
Wiley-VCH, 2023. — 435 p. — ISBN 978-1-119-98599-0. Zeroing Neural Networks Describes the theoretical and practical aspects of finite-time ZNN methods for solving an array of computational problems Zeroing Neural Networks (ZNN) have become essential tools for solving discretized sensor-driven time-varying matrix problems in engineering, control theory, and on-chip applications...
Springer, 2024. — 439 p. — (Springer Series on Bio- and Neurosystems 16). — ISBN 978-3-031-36705-2 This book offers a timely and comprehensive review of the field of neurotronics. Gathering cutting-edge contributions from neuroscientists, biologists, psychologists, as well as physicists, microelectronics engineers and information scientists, it gives extensive information on...
Springer, 2025. — 256 p. — ISBN 978-3-031-68965-9. Mathematical chaos in neural networks is a powerful tool that reflects the world’s complexity and has the potential to uncover the mysteries of the brain’s intellectual activity. Through this monograph, the authors aim to contribute to modern chaos research, combining it with the fundamentals of classical dynamical systems and...
Springer, 2022. — 336 p. This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the...
Academic Press/Elsevier, 2023. — 328 p. State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks (ANN) and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of Machine Learning, Artificial Intelligence (AI), Deep Learning...
Independently published, 2024. — 81 p. — ISBN-13 979-8327132856. Нейронные сети для начинающих: раскройте секреты нейронных сетей. Руководство для начинающих по самому мощному инструменту искусственного интеллекта "Neural Networks for Beginners: Unlock the Secrets of Neural Networks" is your essential guide to understanding and mastering one of artificial intelligence's most...
Springer, 2021. — 545 p. — ISBN 978-3-030-80567-8. This book contains the proceedings of the 22nd EANN “Engineering Applications of Neural Networks” 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing...
Springer, 2024. — 204 p. — (Studies in Computational Intelligence 1146). — ISBN 978-3-031-53712-7. Новые направления создания гибридных интеллектуальных систем на основе нейронных сетей, нечеткой логики и алгоритмов оптимизации We describe in this book new directions on the theoretical developments of fuzzy logic, neural networks, and meta-heuristic algorithms, as well as their...
Springer, 2022. — 123 p. — ISBN 978-3-031-14571-1. This book explains the basic concepts, theory and applications of neural networks in a simple unified approach with clear examples and simulations in the MatLAB programming language. The scripts herein are coded for general purposes to be easily extended to a variety of problems in different areas of application. They are...
Apress, 2021. — 726 p. — ISBN: 1484261496. Develop machine learning models across various domains. This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.
Springer Cham, 2023. — 198 p. — (Synthesis Lectures on Data Mining and Knowledge Discovery). — eBook ISBN 978-3-031-16174-2. This book provides a comprehensive introduction to the foundations and frontiers of graph neural networks. In addition, the book introduces the basic concepts and definitions in graph representation learning and discusses the development of advanced graph...
Springer, 2021. — 276 p. — ISBN: 3662611821, 9783662611821. This book treats essentials from neurophysiology (Hodgkin–Huxley equations, synaptic transmission, prototype networks of neurons) and related mathematical concepts (dimensionality reductions, equilibria, bifurcations, limit cycles and phase plane analysis). This is subsequently applied in a clinical context, focusing...
Springer Singapore, 2024. — 260 p. — (Computational Intelligence Methods and Applications). — eBook ISBN 978-981-99-5068-3. Review recent advances in CNN compression and acceleration Elaborate recent advances on deep model compression technologies Introduce applications of model compression in image classification, speech recognition, object detection etc. Deep learning has...
Packt Publishing, 2019. — 374 p. — ISBN: 978-1-78899-259-6. Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial...
Springer, 2021. — 186 p. — (Studies in Fuzziness and Soft Computing, 408). — ISBN 978-3-030-72279-1. The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient. Fuzzy logic together with...
Springer, 2022. — 435 p. — ISBN 978-3-031-01232-7. Глубокие нейронные сети и данные для автоматизированного вождения This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much...
Bentham Science Publishers, December 19, 2023. — 238 р. — ISBN: 978-981-5165-35-7. This textbook provides a quick and easy understanding of multistage interconnection networks (MINs) for engineers. The book contents focus on the design, performance metrics, and evaluation of these networks which are crucial in modern computer architecture. The contents equip engineering...
IGI Global, 2023. — 267 p. Graph Neural Networks, also known as GNNs, have seen a meteoric rise in popularity over the past few years due to its capacity to analyse data that is shown in the form of graphs. GNNs have been put to use in a broad variety of industries, including social network research, the search for new drugs, recommender systems, and traffic prediction, to...
Packt, 2019. — 368 p. — ISBN: 9781838824914 ncrease the performance of various neural network architectures using NEAT, HyperNEAT, ES-HyperNEAT, Novelty Search, SAFE, and Deep Neuroevolution. Key Features Implement neuroevolution algorithms to improve performance of various neural network architectures Get well-versed with evolutionary algorithms and neuroevolution methods...
Springer, 2024. — 304 p. — (Серия: Computational Intelligence Methods and Applications). — ISBN 978-981-97-5279-9. Membrane computing is a class of distributed and parallel computing models inspired by living cells. Spiking neural P systems are neural-like membrane computing models, representing an interdisciplinary field between membrane computing and artificial neural...
Springer Cham, 2023. — 119 p. — (SpringerBriefs in Computer Science) — eBook ISBN: 978-3-031-39179-8. This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas. This book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frameworks. This would include...
Springer, 2023. — 339 p. — eBook ISBN: 978-981-99-1790-7. Introduces readers to a modern theory of the minimum description length (MDL) principle Includes rich examples of MDL applications to machine learning and data science Written by a pioneer of information-theoretic learning theory This book introduces readers to the minimum description length (MDL) principle and its...
Independently published, 2021. — 186 p. — (Herong's Tutorial Examples). — ISBN 979-8720214708. This book is a collection of notes and sample codes written by the author while he was learning Neural Networks in Machine Learning. Topics include Neural Networks (NN) concepts: nodes, layers, activation functions, learning rates, training sets, etc.; deep playground for classical...
Packt Publishing, 2018 - 272p. - ISBN: 1789130336 Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges. Key Features Learn the fundamentals of Convolutional Neural Networks Harness Python and...
CRC Press, 1997. — 278 p. — ISBN 13: 978-0-7503-0499-3. Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel...
Apress Media, 2025. — 191 p. — ISBN-13: 979-8-8688-1020-6. Нейронные сети с Tensorflow и Keras: обучение, генеративные модели и обучение с подкреплением Explore the capabilities of Machine Learning and neural networks. This comprehensive guidebook is tailored for professional programmers seeking to deepen their understanding of neural networks, Machine Learning (ML) techniques,...
Packt, 2018. — 122 p. — ISBN: 978-1789132335. Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework. Key Features Train and deploy Recurrent Neural Networks using the popular TensorFlow library Apply long short-term...
Springer Singapore, 2025. — 925 p. — eBook ISBN 978-981-97-9933-6. Designs minimum spanning tree based graph construction and integrates GNN with Transformer to improve VOS methods. Improves multi-scale object segmentation performance for scene parsing by self-supervised feature fusion-based GCN. Proposes structure-property based graph representation learning and dynamic GNN...
Packt Publishing Ltd., 2019. — 385 p. — ISBN: 978-1-78913-890-0. Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis,...
Springer Singapore, 2024. — 422 p. — eBook ISBN 978-981-97-9282-5. Discover the cutting-edge of spiking neural P systems, a captivating area of artificial neural network. Provide comprehensive insights into foundations, applications, and implementations of the system. Explore the most dynamic models in membrane computing and delves into the reasons behind. Spiking neural P...
SelfPub, 2023. — 240 с. Книга представляет собой исчерпывающее руководство по применению нейросетей в различных областях анализа текста. С этой книгой читатели отправятся в увлекательное путешествие по миру искусственного интеллекта, где они узнают о бесконечных возможностях, которые предоставляют нейронные сети. Введение В мире, где информация преображается в валовый объем...
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