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This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems.
This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification.
Further, the book shows new directions for cooperation between science and industry and facilitates efficient transfer of knowledge in the area of intelligent information systems.
This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data.
The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using... Læs mere
This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch.
The book trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML... Læs mere
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science.
Data Science in Practice is the ideal introduction to data science. With or without math skills: Here you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be.
The goal of this book is to get leaders and practitioners to start thinking about how they may deploy techniques outside their function or industry into their domain. Application of modern technology into new areas is one of the fastest, most effective ways to improve results.