Applied Mathematics with F#
Springer Nature Switzerland AG (Verlag)
978-981-96-9633-8 (ISBN)
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This book highlights the enormous potential of F#—in comparison to other programming languages—to be used in scientific computing. It presents solutions of diverse real-life problems by using the combination of applied mathematics and F#. The book begins by introducing different generic collections offered by F# and goes on to present their usages in various areas of applied mathematics such as vectors and matrices, descriptive statistics, set theory, probability and calculus. Empowering users to tackle complex computing problems by using succinct yet robust code, F# is very well positioned to be used for applied mathematics; making this book all the more important for interested readers in this area.
The book uses Plotly.NET to create interactive, publication-quality charts and visualizes vector fields, Jacobians, matrices as heatmaps, and probability distributions and KDEs, ordinary differential equations solutions and phase plots. It uses AngouriMath for symbolic differentiation, simplification, and algebra. It also shows how to blend symbolic math with numerical methods like Trapezoidal and Simpson’s rule, Runge–Kutta methods and Gaussian quadrature. The book includes several real-life case studies as examples such as soccer player analytics, housing price analysis, bungee jumper physics simulation, predator–prey ecosystem model and credit score evaluation.
Sudipta Mukherjee is a seasoned software engineer and a recognized F# expert. With over two decades of experience spanning enterprise software development, compiler design and machine learning applications, he is a thought leader in programming language design and static code analysis. He has been honoured with the ”Recognized F# Expert” award by the F# Software Foundation for his contributions to the F# ecosystem. He continues to push the boundaries of what’s possible with functional programming in practical applications. His contributions to the programming community include six acclaimed books ML.NET Revealed (2020), Source Code Analytics (2017), F# for Machine Learning Essentials (2016), Thinking in LINQ (2014), .NET Generics Beginners Guide (2012). His first book, Data Structure using C: 1000 Problems and Solutions (2008), was also translated into Chinese. His latest book, Applied Mathematics with F#, uses functional programming to solve computational challenges in scientific domains. His conference presentations at events like the F# Exchange at London and the Functional Programming Conference at Bangalore, India, have inspired developers worldwide to adopt functional programming paradigms. As the author of “Squirrel”, a cross-platform agile data analytics framework for .NET with over thousands of downloads, Sudipta has demonstrated his ability to create practical solutions for real-world problems.
Chapter 1. F# Collections Walkthrough.- Chapter 2. Exploratory Visualizations.- Chapter 3. Descriptive Statistics.- Chapter 4. Vectors and Matrices.- Chapter 5. Set Theory and Probability.- Chapter 6. Integrations and Differentiations.- Chapter 7. Solving Ordinary Differential Equations.
| Erscheinungsdatum | 29.11.2025 |
|---|---|
| Vorwort | Don Syme, John Azariah |
| Zusatzinfo | 114 Illustrations, color; 40 Illustrations, black and white |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Compilerbau | |
| Mathematik / Informatik ► Mathematik ► Analysis | |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| ISBN-10 | 981-96-9633-X / 981969633X |
| ISBN-13 | 978-981-96-9633-8 / 9789819696338 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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