Machine learning books

This book discusses the interplay between statistics, data science, machine learning and artificial intelligence,...  Read More >>

This book discusses the principles and practical applications of data science, addressing key topics including data...  Read More >>

This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through...  Read More >>

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines...  Read More >>

Named one of 'The five best books to understand AI' by The Economist The impact AI will have is profound, but the...  Read More >>

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production...  Read More >>

The authors present deep learning case studies on all data described.Deep learning models: Neural network models...  Read More >>

Explainability methods provide an essential toolkit for better understanding model behavior, and this practical...  Read More >>

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This book presents collection of research papers presented at International Conference on Information and Communication...  Read More >>

This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning...  Read More >>

This book includes high-quality research papers presented at the Fifth International Conference on Innovative Computing...  Read More >>

This is an open access book. The focus of the conference is to provide a unique platform for exchange of ideas and...  Read More >>

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics,...  Read More >>

This book explores the application of data mining and machine learning techniques in studying the activity pattern,...  Read More >>

This book presents an exploration of linkages among soil-water, agriculture, and climate change with a special focus...  Read More >>

This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL)...  Read More >>

This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented...  Read More >>

Creative AI defines art and media practices that have AI embedded into the process of creation, but also encompass...  Read More >>

Eventually, open issues and future work on QA are discussed in Chapter 9.This book delivers a comprehensive overview...  Read More >>

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th...  Read More >>

This book meets the present and future needs for the interaction between various science and technology/engineering...  Read More >>

Designed with engineers in mind, this self-contained book will equip students with everything they need to apply...  Read More >>

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Line intensity mapping (LIM) is an observational technique that probes the large-scale structure of the Universe...  Read More >>