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  • Sách/Book

  • Discrete Mathematics and Its Applications

    • Authors: Kenneth H. Rosen (2019)

  • This new edition of the book includes many enhancements, updates, additions, and edits, alldesigned to make the book a more effective teaching tool for a modern discrete mathematics course. Instructors who have used the book previously will notice overall changes that have been made throughout the book, as well as specific changes.
  • Sách/Book

  • Discrete Mathematics with Applications

    • Authors: Susanna S. Epp (2019)

  • DISCRETE MATHEMATICS WITH APPLICATIONS, 5th Edition, explains complex, abstract concepts with clarity and precision and provides a strong foundation for computer science and upper-level mathematics courses of the computer age. Author Susanna Epp presents not only the major themes of discrete mathematics.
  • Sách/Book

  • Elementary Differential Equations and Boundary Value Problems

    • Authors: William Boyce (2019)

  • The 10th edition of Elementary Differential Equations and Boundary Value Problems , like its predecessors, is written from the viewpoint of the applied mathematician, whose interest in differential equations may sometimes be quite theoretical, sometimes intensely practical, and often somewhere in between.
  • Sách/Book

  • Ordinary Differential Equations: An Introduction to the Fundamentals

    • Authors: Kenneth B. Howell (2019)

  • The Second Edition of Ordinary Differential Equations: An Introduction to the Fundamentals builds on the successful First Edition. It is unique in its approach to motivation, precision, explanation and method. Its layered approach offers the instructor opportunity for greater flexibility in coverage and depth.
  • Sách/Book

  • An introduction to categorical data analysis

    • Authors: Alan Agresti (2019)

  • Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data.
  • Sách/Book

  • JavaScript Data Structures and Algorithms

    • Authors: Sammie Bae (2019)

  • This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching.
  • Sách/Book

  • Probability and statistics for data science : math + R + data

    • Authors: Norman Matloff (2019)

  • Probability and Statistics for Data Science: Math + R + Data covers "math stat"-distributions, expected value, estimation etc.-but takes the phrase "Data Science" in the title quite seriously: Real datasets are used extensively. All data analysis is supported by R coding. Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.
  • Sách/Book

  • Probability and statistics for computer scientists

    • Authors: Michael Baron (2019)

  • Probability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB
  • Sách/Book

  • An elementary approach to design and analysis of algorithms

    • Authors: Lekh Raj Vermani (2019)

  • This book introduces a set of concepts in solving problems computationally such as Growth of Functions; Backtracking; Divide and Conquer; Greedy Algorithms; Dynamic Programming; Elementary Graph Algorithms; Minimal Spanning Tree; Single-Source Shortest Paths; All Pairs Shortest Paths; Flow Networks; Polynomial Multiplication, to ways of solving NP-Complete Problems, supported with comprehensive, and detailed problems and solutions, making it an ideal resource to those studying computer science, computer engineering and information technology.