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Results 671-680 of 3082 (Search time: 0.132 seconds).
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  • Sách/Book

  • Prime Numbers and Computer Methods for Factorization

    • Authors: Hans Riesel (2012)

  • The book treats four fundamental problems: the number of primes below a given limit, the approximate number of primes, the recognition of primes and the factorization of large numbers. The author provides explicit algorithms and computer programs, and has attempted to discuss as many of the classically important results as possible, as well as the most recent discoveries.
  • Sách/Book

  • Convex Analysis and Global Optimization

    • Authors: Hoang Tuy (2016)

  • The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come.
  • Sách/Book

  • An Introduction to Nonstandard Real Analysis

    • Authors: Albert Hurd (1995)

  • The main addition of this book to the contributions of previous textbooks on nonstandard analysis (12,37,42,46) is the first chapter, which eases the reader into the subject with an elementary model suitable for the calculus, and the fourth chapter on measure theory in nonstandard models.
  • Sách/Book

  • A Concrete Introduction to Real Analysis

    • Authors: Robert Carlson (2018)

  • The standard, austere approach to teaching modern mathematics with its emphasis on formal proofs can be challenging and discouraging for many students. To remedy this situation, the new edition is more rewarding and inviting. Students benefit from the text by gaining a solid foundational knowledge of analysis, which they can use in their fields of study and chosen professions.
  • Sách/Book

  • Machine Learning Engineering

    • Authors: Andriy Burkov (2020)

  • The Machine Learning Engineering for Production (MLOps) Specialization covers how to conceptualize, build, and maintain integrated systems that continuously operate in production. In striking contrast with standard machine learning modeling, production systems need to handle relentless evolving data. Moreover, the production system must run non-stop at the minimum cost while producing the maximum performance. In this Specialization, you will learn how to use well-established tools and methodologies for doing all of this effectively and efficiently.
  • Sách/Book

  • Elementary Differential Equations and Boundary Value Problems

    • Authors: William E. Boyce (2020)

  • The authors have sought to combine a sound and accurate (but not abstract) exposition of the elementary theory of differential equations with considerable material on methods of solution, analysis, and approximation that have proved useful in a wide variety of applications.
  • Sách/Book

  • Univariate, bivariate, and multivariate statistics using R : quantitative tools for data analysis and data science

    • Authors: Daniel J. Denis (2020)

  • This book provides a user-friendly and practical guide on R, with emphasis on covering a broader range of statistical methods than previous books on R. This is a "how to" book and will be of use to undergraduates and graduate students along with researchers and professionals who require a quick go-to source to help them perform essential statistical analyses and data management tasks in R. The book only assumes minimal prior knowledge of statistics, providing readers with the tools they need right now to help them understand and interpret their data analyses. This book covers univariate, bivariate, and multivariate statistical methods, as well as some nonparametric tests.