Numerical Methods Using Kotlin

For Data Science, Analysis, and Engineering
1. Auflage 2023
ISBN: 978-1-4842-8825-2
Verlag: Apress

Buch, Englisch, 899 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1699 g

This in-depth guide 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.
In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you’ll see how it can help you easily create solutions for your complex engineering and data science problems.
After reading this book, you'll come away with the knowledge to create your own numerical models and algorithms using the Kotlin programming language.
What You Will Learn - Program in Kotlin using a high-performance numerical library
- Learn the mathematics necessary for a wide range of numerical computing algorithms
- Convert ideas and equations into code
- Put together algorithms and classes to build your own engineering solutions
- Build solvers for industrial optimization problems
- Perform data analysis using basic and advanced statistics
Who This Book Is For
Programmers, data scientists, and analysts with prior experience programming in any language, especially Kotlin or Java.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Li

Li, PhD, Haksun

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

1: Introduction to Numerical Methods in Kotlin.- 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.

Über Autor(innen)

Haksun Li, PhD, is founder of NM Group, a scientific and mathematical research company. He has the vision of “Making the World Better Using Mathematics”. Under his leadership, the firm serves worldwide brokerage houses and funds, multinational corporations and very high net worth individuals. Haksun is an expert in options trading, asset allocation, portfolio optimization and fixed-income product pricing. He has coded up a variety of numerical software, including SuanShu (a library of numerical methods), NM Dev (a library of numerical methods), AlgoQuant (a library for financial analytics), NMRMS (a portfolio management system for equities), and supercurve (a fixed-income options pricing system). Prior to this, Haksun was a quantitative trader/quantitative analyst with multiple investment banks. He has worked in New York, London, Tokyo, and Singapore. Additionally, Haksun is the vice dean of the Big Data Finance and Investment Institute of Fudan University, China. He was an adjunct professor with multiple universities. He has taught at the National University of Singapore (mathematics), Nanyang Technological University (business school), Fudan University (economics), as well as Hong Kong University of Science and Technology (mathematics). Dr. Haksun Li has a B.S. and M.S. in pure and financial mathematics from the University of Chicago, and an M.S. and a PhD in computer science and engineering from the University of Michigan, Ann Arbor.