Programs related to the field of Computer Science are expessed here. More on Computer Science is at the following link: https://www.pinterest.com/HamedShahHosseini/

1. Determinant from scratch with Python by converting matrix to triangular one.
2. Cramer's rule for solving a system of linear equations.
3. Matrix inversion by the cofactor matrix from scratch in Python.
4. Matrix inversion by Gauss-Jordan elimination from scratch in Python.
5. Fast Fourier Transform (FFT), one-dimensional, from scratch in Python. Also, Discrete Fourier Transform (DFT) from scratch is also included.
6. Divide and Conquer: Quicksort from scratch in Python.
7. Dynamic Programming: Fibonacci numbers in Python.
8. Singly Linked Lists from scratch with Python. An example is also given to implement a stack having functions: push and pop.
9. Complex numbers: introduction. Here, we review complex numbers in both rectangular and polar forms by reminding Euler's formula and De Moivre's formula. Also, we review doing arithmetic for complex numbers in Python.
10. Absolute and relative errors are reviewed. When we don't know the true value, we may use approximate value in measuring the mentioned errors. A Python example is also provided.
11. Root finding, Bisection method: It is a bracketing method to find one root of a continuous function, given the interval [a,b] in which the root exists. It is assumed that f(a)f(b)<0.
12. Root finding, False Position method: This root finding method is also a bracketing method with the same assumptions we make for the bisection method. However, it is usually faster than the bisection method.
13. Root finding, Fixed Point Iteration: This is an open method such that it starts by an initial guess of the root, and then it uses an iteration to get closer to the real root.
14. Root finding, Secant method: We give two initial guesses of the root. Then, the method creates a secant line which intersects the x-axis at a value that is usually a better estimate of the root.