Portfolio

SVM

SVM uses python along with scikit-learn to identify 10 features and accurately predict the labels between 7 different types of glass in the UCI glass data set through the use of Support Vector Machines. This program uses five crossfold validation and spilts the data intro three sets to maximize the hyperparameters for the test dataset and compares the performance on the different types of Support Vector Machines

Language: Python / scikit-learn

Hangman

Hangman uses the Cozmo SDK and command line input to have Anki’s Cozmo robot host an interactive game of hangman

Language: Python / Cozmo sdk

Fibonacci

Fibonacci uses 2 input files Fibonacci.c and the testcase files to demonstrate the parsing of both an int and a string to a HugeInteger struct as well as calculating the Fibonacci sequence to the 1000th term in O (nk) time. Where n is the parameter passed to the function and k is the number of digits in F(n)

Language: C

Highest Score

Highest Score uses 2 input files Hw03.java and the contest_.in files to use dynamic programming and determine the optimum problem list to tackle. To gain the most points with the least amount of time having to fully solve the problems

Language: Java

Skip List

Skip List uses 2 input files Hw02.java and the H2in-_#.txt files to build a skip list data structure to support the traversal, searching, addition and deletion of integers. This implementation supports building a skip list to support some number of occurrences of integers in the range of 1 to 1000

Language: JAVa