Example 1: Matrix Multiplication Pseudocode def multiply(lns, rhs): # let result be a lhs.rows by rhs.columns matrix for i in 0...result.rows for j in 0...result.cols for k in 0...1hs.cols result[i][j] = lhs[i][k] * rhs[k][j] return result If you did not finish implementing this code. In this assignment you will: 1. Select a programming language (C++14+ or Python 3.7+ are strongly encouraged). 2. Reformulate pseudocode for use with your selected language 3. Implement the refined pseudocode in your selected language 2 Purpose As a Computer Science student, you have been various software design methodologies (e.g. stepwise refinement) and mathematical problems (e.g.. systems of equations as matrices). In this exercise you will take pseudocode, implement it, and analyze its complexity (temporal and spatial). 3 What to Do 1. Start by creating a ReadMe file (either .md or .txt). Use the provided template to start your required ReadMe: Example 2: Sample ReadMe.md # Getting Started **Language: ** selected_language_here:} # My Pseudocode {insert pseudocode here} # Requirements {List dependencies and libraries here) # Compilation & Execution Instructions {list required commands} Each {} represents a placeholder for your content. 2. Complete, document, and test your matrix multiplication code. 3. Take the Gaussian Elimination Pseudocode discussed in The Initial Pseudocode section and rewrite it to work with your selected language and data structures. 4. Place your finalized pseudocode under # My Pseudocode in your ReadMe file. 5. Implement a matrix solver, based on your updated pseudocode. 6. When you are done... save this code. If you are careful, you will have a significant chunk of code you need for the semester project! A library you can use with a quick C++ #include {} or Java import {} or Python from {} import {} is your goal. 7. Package your ReadMe file, source code, and build configuration into a single zip file or tarball. 3.1 Input For this exercise you may hardcode the initialization of your X, XT. and Y matrices. Use the matrices from Quadratic Example as your inputs. 3.2 Output Your output should be a single line in the form phi_hat = c_0 + C_1 * x + c_2 * x^2 where c_, C_1, and c_2 are the coefficients computed by your code