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...
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...
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...
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...
Apress Media LLC, 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)...
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, 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...
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...
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 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,...
JohnWiley&Sons,Inc., 2023. — 240 p. — ISBN-978-1119901990. 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...
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...
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...
Taylor & Francis Group, LLC, 2020. — 248 p. — ISBN: 978-0-429-43129-6 (ebk). 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...
Packt Publishing, 2019. — 462 p. — ISBN13: 978-1-78953-608-9. 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...
CreateSpace, 2016. — 222 p. A step-by-step 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...
Apress Media LLC., 2020. — 749 p. — ISBN13: (pbk): 978-1-4842-6149-1. 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. After learning what's new in TensorFlow 2, you'll dive right into developing machine learning...
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...
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...
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...
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