Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.This comprehensive textbook is th...

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of...

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading i...

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...

Get to grips with the basics of Keras to implement fast and efficient deep-learning modelsKey FeaturesImplement various deep learning algorithms in Keras and see how deep learning can be used in gamesSee how various deep learning models and practical use-cases can be implemented using KerasA practical, hands-on guide with real-world examples to give you a strong foundation in KerasBook DescriptionThis book starts by introduci...

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach...

Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries.Key FeaturesSecond edition of the bestselling book on Machine LearningA practical approach to key frameworks in data science, machine learning, and deep learningUse the most powerful Python libraries to implement machine learning and deep learningGet to know the best practices to improve and optimize you...

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.Key Features\[\*\] Explore and create intelligent systems using cutting-edge deep learning techniques\[\*\] Implement deep learning algorithms and work with revolutionary libraries in Python\[\*\] Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreBook DescriptionWith an incr...

Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding p...

Impossible Minds: My Neurons, My Consciousness has been written to satisfy the curiosity each and every one of us has about our own consciousness. It takes the view that the neurons in our heads are the source of consciousness and attempts to explain how this happens. Although it talks of neural networks, it explains what they are and what they do in such a way that anyone may understand. While the topic is partly philosophical, the text makes no assumptions of prior knowledge of philosoph...

Machine Dreaming and Consciousness is the first book to discuss the questions raised by the advent of machine dreaming. Artificial intelligence (AI) systems meeting criteria of primary and self-reflexive consciousness are often utilized to extend the human interface, creating waking experiences that resemble the human dream. Surprisingly, AI systems also easily meet all human-based operational criteria for dreaming. These "dreams are far different from anthropomorphic dreaming, including s...

From ecosystems to Facebook, from the Internet to the global financial market, some of the most important and familiar natural systems and social phenomena are based on a networked structure. It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and...