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  • Sách/Book

  • Multivariate data analysis

    • Authors: Joseph F. Hair (-)

  • The eighth edition of Multivariate Data Analysis provides an updated perspective on the analysis of all types of data as well as introducing some new perspectives and techniques that are foundational in today’s world of analytics. Multivariate Data Analysis serves as the perfect companion for graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques.
  • 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.
  • Sách/Book

  • Data Science for Business and Decision Making : An Introductory Text for Students and Practitioners

    • Authors: Seyed Ali Fallahchay (2020)

  • This book explores the principles underpinning data science. It considers the how and why of modern data science. The book goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making. Using real life examples, this book explores the possibilities and limitations of an information-based decision making framework.
  • Sách/Book

  • Analysis of Doubly Truncated Data : An Introduction

    • Authors: Achim Doerre (2019)

  • This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods.
  • Sách/Book

  • Multi-Objective Optimization using Artificial Intelligence Techniques

    • Authors: Seyedali Mirjalili (2020)

  • This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them.
  • Sách/Book

  • Deep learning with PyTorch

    • Authors: Eli Stevens (2020)

  • Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. After covering the basics, you’ll learn best practices for the entire deep learning pipeline, tackling advanced projects as your PyTorch skills become more sophisticated.