Created a program to generate an n-degree polynomial of best fit for any given
data set
Developed several methods to compute vector and matrix operations that are not
built-in to NumPy such as the Gram-Schmidt process, computing vector length, and
vector projections
Created a library of common data structures, algorithms, and interview questions
in Python
Built implementations of stacks, queues, linked-lists, trees, graphs, sets, etc.
Included examples of algorithmic approaches such as divide and conquer, dynamic
programming, greedy, search, sorting, selection, and linear programming
