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Will Fritz's Projects

apriori-algorithm icon apriori-algorithm

The Apriori algorithm detects frequent subsets given a dataset of association rules. This Python 3 implementation reads from a csv of association rules and runs the Apriori algorithm

basketball-reference-scraper icon basketball-reference-scraper

Web Scraper to get the names of teams in each round of the mens NCAA march madness tournament from sports-reference for a specific year

data-structures-examples icon data-structures-examples

Contains a variety of projects which involve the utilization of Data Structures in C++. Follows many aspects of object-oriented design through the use of classes/inheritance/polyorphism

decision-tree icon decision-tree

Python 3 implementation of decision trees using the ID3 and C4.5 algorithms. ID3 uses Information Gain as the splitting criteria and C4.5 uses Gain Ratio

flask-app-in-docker icon flask-app-in-docker

Simple implementation of working flask app with a database. Utilizes docker for each microservice

frogger icon frogger

Replica of the game classic game Frogger using C++ and the SDL library

http-server icon http-server

Uses low-level system calls related to sockets and networking to make a HTTP client and server

intro-cpp-examples icon intro-cpp-examples

Collection of C++ programs written for a an intro to c++ class. Range from introductory C++ to object-oriented projects

nba-playoff-pred-r icon nba-playoff-pred-r

Cluster-specific logistic regression models for whether an NBA team will make the playoffs given the current statistics of that team. Specifically uses population averaged models (PA) based on generalized estimating equations (GEE); Also, uses cluster-specific (each team) random effects models

numerical-methods icon numerical-methods

Contains sample implementations in python of the following numerical methods: Euler's Method, Midpoint Euler's Method, Runge Kuttta Method of Order 4, and Composite Simpson's Rule

player-stats-vs-opp-api icon player-stats-vs-opp-api

An RESTful API that allows users to obtain statistics for an individual NBA player against a specific team in the NBA. This type of data is particularly useful for daily fantasy games

root-finding-methods icon root-finding-methods

Utilizing root-finding methods such as Bisection Method, Fixed-Point Method, Secant Method, and Newton's Method to solve for the roots of functions

search icon search

Recursively searches a directory and prints items it finds based on the specified options. Implemented in C and uses low-level system calls

snake-game icon snake-game

c++ implementation of the classic snake game using gfx library.

tcp-chatroom icon tcp-chatroom

A client and server model written in C/C++. The server hosts multiple concurrent clients. The clients can choose to message everyone in the chat or direct message certain users.

tcp-pong-game icon tcp-pong-game

Implementation of the classic game 'Pong' in C/C++. The game is played over a network, all that is needed is the binary 'netpong' on each machine

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