Numerical Methods Using Java : For Data Science, Analysis, and Engineering

Book Cover
Average Rating
Author
Li, Haksun.
Published
New York, NY : Apress, [2022].
Status
Available Online

Description

Implement numerical algorithms in Java using NM Dev, an object-oriented and high-performance programming library for mathematics. You'll see how it can help you easily create a solution for your complex engineering problem by quickly putting together classes. Numerical Methods Using Java covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. What You Will Learn Program in Java using a high-performance numerical library Learn the mathematics for a wide range of numerical computing algorithms Convert ideas and equations into code Put together algorithms and classes to build your own engineering solution Build solvers for industrial optimization problems Do data analysis using basic and advanced statistics Who This Book Is For Programmers, data scientists, and analysts with prior experience with programming in any language, especially Java.

More Details

Format
Language
English
ISBN
1484267974, 9781484267974
UPC
10.1007/978-1-4842-6797-4

Notes

Bibliography
Includes bibliographical references and index.
Description
Implement numerical algorithms in Java using NM Dev, an object-oriented and high-performance programming library for mathematics. You'll see how it can help you easily create a solution for your complex engineering problem by quickly putting together classes. Numerical Methods Using Java covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. What You Will Learn Program in Java using a high-performance numerical library Learn the mathematics for a wide range of numerical computing algorithms Convert ideas and equations into code Put together algorithms and classes to build your own engineering solution Build solvers for industrial optimization problems Do data analysis using basic and advanced statistics Who This Book Is For Programmers, data scientists, and analysts with prior experience with programming in any language, especially Java.
Local note
O'Reilly O'Reilly Online Learning: Academic/Public Library Edition

Table of Contents

1: Introduction to Numerical Methods in Java
2: Linear Algebra
3: Finding Roots of Equations
4: Finding Roots of Systems of Equations
5: Curve Fitting and Interpolation
6: Numerical Differentiation and Integration
7: Ordinary Differential Equations
8: Partial Differential Equations
9: Unconstrained Optimization
10: Constrained Optimization
11: Heuristics
12: Basic Statistics
13: Random Numbers and Simulation
14: Linear Regression
15: Time Series Analysis
References.

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Citations

APA Citation, 7th Edition (style guide)

Li, H. (2022). Numerical Methods Using Java: For Data Science, Analysis, and Engineering . Apress.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Li, Haksun. 2022. Numerical Methods Using Java: For Data Science, Analysis, and Engineering. New York, NY: Apress.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Li, Haksun. Numerical Methods Using Java: For Data Science, Analysis, and Engineering New York, NY: Apress, 2022.

Harvard Citation (style guide)

Li, H. (2022). Numerical methods using java: for data science, analysis, and engineering. New York, NY: Apress.

MLA Citation, 9th Edition (style guide)

Li, Haksun. Numerical Methods Using Java: For Data Science, Analysis, and Engineering Apress, 2022.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID
7b7995af-7c7f-bb89-89b3-b451ec7e563f-eng
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Grouped Work ID7b7995af-7c7f-bb89-89b3-b451ec7e563f-eng
Full titlenumerical methods using java for data science analysis and engineering
Authorli haksun
Grouping Categorybook
Last Update2025-01-24 12:33:29PM
Last Indexed2025-03-27 03:19:12AM

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Last UsedFeb 19, 2025

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