Neural Networks

Have over a hundred years of brain research revealed all its secrets? This book is motivated by a realization that cortical structure and behavior can be explained by a synergy of seemingly different mathematical notions: global attractors, which define...

Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key Features Gain a practical understanding of deep learning using Golang Build complex neural network models using Go libraries and Gorgonia Take your deep...

Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen Think about the benefits of automating tedious business processes and back-office tasks Consider the competitive...

Diagnosis through images, robot surgeons, digital twins, and the metaverse are some of the applications in which artificial intelligence (AI) is involved. It is an almost sci-fi world that touches us closely and toward which we can harbor both great...

After many years during which it languished in relative obscurity - in remote classrooms of computer science departments and in small prototype projects for tech companies - AI is now a searingly hot topic across the media. Yet much of the public...

Diagnosis through images, robot surgeons, digital twins, and the metaverse are some of the applications in which Artificial Intelligence (AI) is involved. An almost sci-fi world that touches us closely and towards which we can harbour great hopes and...

If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives...

Expansive overview of theory and practical implementation of networks in investment management Guided by graph theory, Network Models in Finance: Expanding the Tools for Portfolio and Risk Management provides a comprehensive overview of networks in...

Deep Learning in Diabetes Mellitus Detection and Diagnosis focuses on deep learning-based approaches in the field of diabetes mellitus detection and diagnosis, including preprocessing techniques that are an essential part of this subject. This is the...

Entropy Randomization in Machine Learning presents a new approach to machine learning—entropy randomization—to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study). Randomized machine-learning procedures...

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...