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  • Sách/Book

  • Machine Learning with R

    • Authors: Abhijit Ghatak (2017)

  • This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it's applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning
  • Sách/Book

  • Combinatorial optimization : theory and algorithms

    • Authors: Bernhard Korte (2012)

  • This fifth edition has again been updated, revised, and significantlyextended, with more than 60 new exercises and new material on varioustopics, including Cayley's formula, blocking flows, faster"b"-matching separation, multidimensional knapsack, multicommoditymax-flow min-cut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.
  • Sách/Book

  • Introduction to the Theory of Statistical Inference

    • Authors: Hannelore Liero (2011)

  • Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory
  • Sách/Book

  • Business Result Pre- Intermediate: teacher's book

    • Authors: Rachel Appleby (2018)

  • This section not only provides information on the teaching points covered in the unit, but also offers some background information on the main business theme of the unit and its importance in the current business world. If you are less familiar with the world of business, you will find this section especially helpful to read before starting a unit.
  • Sách/Book

  • Introduction to mathematical statistics

    • Authors: Robert V. Hogg (2013)

  • Introduction to Mathematical Statistics, Seventh Edition, offers a proven approach designed to provide you with an excellent foundation in mathematical statistics. Ample examples and exercises throughout the text illustrate concepts to help you gain a solid understanding of the material.
  • Sách/Book

  • Fuzzy Set Theory―and Its Applications

    • Authors: Hans-Jürgen Zimmermann (2012)

  • This introduction to fuzzy set theory and its multitude of applications seeks to balance the character of the book with the dynamic nature of the research. This edition includes new chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research. Existing material has been updated, and extended exercises are included.
  • Sách/Book

  • A Course in Number Theory and Cryptography

    • Authors: Neal Koblitz (2012)

  • This is a substantially revised and updated introduction to arithmetic topics, both ancient and modern, that have been at the centre of interest in applications of number theory, particularly in cryptography. As such, no background in algebra or number theory is assumed, and the book begins with a discussion of the basic number theory that is needed
  • Sách/Book

  • Introduction to Mathematical Statistics and Its Applications

    • Authors: Richard J. Larsen (2013)

  • The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.
  • Sách/Book

  • Methods In Behavioral Research

    • Authors: Paul C. Cozby (2011)

  • Highlights of the new edition include a broader introduction of different research techniques in Chapter 4, extensive revision of the 'validity of measurements' section, and updated structural equations models.
  • Sách/Book

  • Introduction to mathematical statistics

    • Authors: Robert V. Hogg (2018)

  • Introduction to Mathematical Statistics by Hogg, McKean, and Craig enhances student comprehension and retention with numerous, illustrative examples and exercises. Classical statistical inference procedures in estimation and testing are explored extensively, and the text’s flexible organization makes it ideal for a range of mathematical statistics courses.