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

## Description

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## 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

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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. Apress.

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

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

**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.

## Staff View

Grouped Work ID

7b7995af-7c7f-bb89-89b3-b451ec7e563f-eng

#### Grouping Information

Grouped Work ID | 7b7995af-7c7f-bb89-89b3-b451ec7e563f-eng |
---|---|

Full title | numerical methods using java for data science analysis and engineering |

Author | li haksun |

Grouping Category | book |

Last Update | 2024-10-08 10:55:34AM |

Last Indexed | 2024-10-16 03:21:08AM |

#### Book Cover Information

Image Source | contentCafe |
---|---|

First Loaded | Aug 13, 2023 |

Last Used | Oct 5, 2024 |

#### Marc Record

First Detected | Mar 20, 2023 10:15:07 AM |
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Last File Modification Time | Mar 20, 2023 10:15:07 AM |

Suppressed | Record had no items |

### MARC Record

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505 | 0 | |a 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. | |

520 | |a 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. | ||

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