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Results 31-40 of 97 (Search time: 0.118 seconds).
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  • Sách/Book

  • Handbook of Discrete and Combinatorial Mathematics

    • Authors: Kenneth H. Rosen (2018)

  • Handbook of Discrete and Combinatorial Mathematics provides a comprehensive reference volume for mathematicians, computer scientists, engineers, as well as students and reference librarians.
  • 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

  • Introduction to probability and statistics for engineers and scientist

    • Authors: Sheldon M. Ross (2021)

  • This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.
  • 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

  • Business statistics in practice : using modeling, data, and analytics

    • Authors: Bruce L. Bowerman (2017)

  • The textbook employs realistic examples, continuing case studies and a business improvement theme to teach the material. The Eighth Edition features more concise and lucid explanations, an improved topic flow and a sensible use of the best and most compelling examples.
  • Sách/Book

  • Introduction to probability and statistics for engineers and scientist

    • Authors: Sheldon M. Ross (2009)

  • As with the previous editions, Ross' text has remendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications apply probability theory to everyday statistical problems and situations