Neural networks and fuzzy systems Books

Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural...

Networks of Learning Automata: Techniques for Online Stochastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures...

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more...

Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret textKey FeaturesUnderstand how to implement deep learning with TensorFlow and KerasLearn the fundamentals of computer vision and...

Take a comprehensive and step-by-step approach to understanding machine learningKey FeaturesDiscover how to apply the scikit-learn uniform API in all types of machine learning modelsUnderstand the difference between supervised and unsupervised learning...

Get a head start in the world of AI and deep learning by developing your skills with PyTorchKey FeaturesLearn how to define your own network architecture in deep learningImplement helpful methods to create and train a model using PyTorch syntaxDiscover...

Implementing supervised, unsupervised, and generative deep learning (DL) models using Keras and Dopamine over TensorFlow.Key FeaturesUnderstand the fundamental machine learning concepts useful in deep learningLearn the underlying mathematical concepts as...

Learn how to use AI and blockchain to build decentralized intelligent applications (DIApps) that overcome real-world challengesKey FeaturesUnderstand the fundamental concepts for converging artificial intelligence and blockchainApply your learnings to...

Develop Bayesian Deep Learning models to help make your own applications more robust.Key Features:Gain insights into the limitations of typical neural networksAcquire the skill to cultivate neural networks capable of estimating uncertaintyDiscover how to...

Discover how to leverage Keras, the powerful and easy-to-use open source Python library for developing and evaluating deep learning modelsKey FeaturesGet to grips with various model evaluation metrics, including sensitivity, specificity, and AUC...

Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces.Key FeaturesLearn explainable...

With knowledge and information shared by experts, take your first steps towards creating scalable AI algorithms and solutions in Python, through practical exercises and engaging activitiesKey FeaturesLearn about AI and ML algorithms from the perspective...

Cut through the noise and get real results with this workshop for beginners. Use a project-based approach to exploring machine learning with TensorFlow and Keras.Key FeaturesUnderstand the nuances of setting up a deep learning programming environmentGain...

Learning how to apply unsupervised algorithms on unlabeled datasets from scratch can be easier than you thought with this beginner’s workshop, featuring interesting examples and activitiesKey FeaturesGet familiar with the ecosystem of unsupervised...

Brainwaves of Dread delves into the terrifying intersections of neuroscience and horror. Through a series of chilling narratives, the book explores the dark side of the human brain, where scientific experimentation and neurological anomalies unleash...

"Get ready to unlock your full potential with ChatGPT! In this comprehensive guide, you'll discover the power of prompt engineering to boost your creativity, productivity, and effectiveness in various niches such as writing, music, business, health,...

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python librariesKey FeaturesBuild a strong foundation in neural networks and deep learning with Python librariesExplore advanced deep learning techniques and...

Simulation of brain neurons in real-time using biophysically-meaningful models is a pre-requisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments...

Ready to throw your hat into the AI and machine learning ring? Get started right here, right now! Are you sick of these machine-learning guides that don't really teach you anything?  Do you already know Python, but you're looking to expand your...

Dive into the "AI Mastery Trilogy," the ultimate collection for professionals seeking to conquer the world of artificial intelligence (AI). This 3-in-1 compendium is meticulously crafted to guide you from the foundational principles of AI to the...

Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological...

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass...

Get started with GPT-3 and the OpenAI API for natural language processing using JavaScript and PythonKey Features:Understand the power of potential GPT-3 language models and the risks involvedExplore core GPT-3 use cases such as text generation,...

The development of solar energy is becoming increasingly widespread all over the world. One significant way to reduce the cost of energy generated by solar modules, as well as reduce the need for centralized energy supply, is the use of non-tracking...

Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and...

As environmental issues remain at the forefront of energy research, renewable energy is now an all-important field of study. And as smart technology continues to grow and be refined, its applications broaden and increase in their potential to...

Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine...

Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases,...

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in...

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge...

In today's modernized market, various disciplines continue to search for universally functional technologies that improve upon traditional processes. Artificial neural networks are a set of statistical modeling tools that are capable of processing...

While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the...

Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to...

Competition in today's global market offers strong motivation for the development of sophisticated tools within computer science. The neuron multi-functional technology platform is a developing field of study that regards the various interactive...

Moving well beyond simply speeding up computation, this book tackles AI for Finance from a range of perspectives including business, technology, research, and students. Covering aspects like algorithms, big data, and machine learning, this book answers...

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...

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things networks.It focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and...