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Numerical Methods Using Kotlin - For Data Science, Analysis, and Engineering (Paperback, 1st ed.)
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Numerical Methods Using Kotlin - For Data Science, Analysis, and Engineering (Paperback, 1st ed.)
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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.
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