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

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.-
References.

Table of ContentsAbout the Authors...........................................................................................................iPreface............................................................................................................................ii1. Why Kotlin?..............................................................................................................61.1. Kotlin in 2022.....................................................................................................61.2. Kotlin vs. C++....................................................................................................61.3. Kotlin vs. Python................................................................................................61.4. Kotlin in the future .............................................................................................62. Data Structures.......................................................................................................72.1. Function...........................................................................................................72.2. Polynomial ......................................................................................................73. Linear Algebra .......................................................................................................83.1. Vector and Matrix ...........................................................................................83.1.1. Vector Properties .....................................................................................83.1.2. Element-wise Operations.........................................................................83.1.3. Norm ........................................................................................................93.1.4. Inner product and angle ...........................................................................93.2. Matrix............................................................................................................103.3. Determinant, Transpose and Inverse.............................................................103.4. Diagonal Matrices and Diagonal of a Matrix................................................103.5. Eigenvalues and Eigenvectors.......................................................................103.5.1. Householder Tridiagonalization and QR Factorization Methods..........103.5.2. Transformation to Hessenberg Form (Nonsymmetric Matrices)...........104. Finding Roots of Single Variable Equations .......................................................114.1. Bracketing Methods ......................................................................................114.1.1. Bisection Method ...................................................................................114.2. Open Methods...............................................................................................11