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  • Sách/Book

  • Learning and soft computing : support vector machines, neural networks, and fuzzy logic models

    • Authors: Vojislav Kecman (2021)

  • This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and compute...
  • Sách/Book

  • Visual thinking for information design

    • Authors: Colin Ware (2022)

  • Visual Thinking for Design, to more accurately reflect its focus on infographics, this timely revision has been updated throughout and includes more content on pattern perception, the addition of new material illustrating color assimilation, and a new chapter devoted to communicating ideas through images.
  • Sách/Book

  • Computer Security and the Internet : Tools and Jewels

    • Authors: Paul C. van Oorschot (2020)

  • This book provides a concise yet comprehensive overview of computer and Internet security, suitable for a one-term introductory course for junior/senior undergrad or first-year graduate students.
  • Sách/Book

  • Convex Analysis for Optimization (Graduate Texts in Operations Research)

    • Authors: Jan Brinkhuis (2020)

  • The book introduces a systematic three-step method for doing everything, which can be summarized as "conify, work, deconify". It starts with the concept of convex sets, their primal description, constructions, topological properties and dual description, and then moves on to convex functions and the fundamental principles of convex optimization and their use in the complete analysis of convex optimization problems by means of a systematic four-step method.
  • Sách/Book

  • Foundations of data science

    • Authors: Avrim Blum (2020)

  • This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing
  • Sách/Book

  • Artificial Intelligence : A National Strategic Initiative

    • Authors: Tencent Research Institute (2021)

  • This book begins with the past and present of the subversive technology of artificial intelligence, clearly analyzes the overall picture, latest developments and development trends of the artificial intelligence industry, and conducts in-depth research on the competitive situation of various countries
  • Sách/Book

  • An Introduction to Computing with Fuzzy Sets

    • Authors: Witold Pedrycz (2021)

  • This book provides concise yet thorough coverage of the fundamentals and technology of fuzzy sets. Readers will find a lucid and systematic introduction to the essential concepts of fuzzy set-based information granules, their processing and detailed algorithms.