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activity-recognition-from-accelerometer-data

Machine learning task to predict participant's activity given data produced by an accelerometer worn on their chest. Includes both local training and Sagemaker training options.

airport-lookup-system

The project aims to design and implement a three-tiered client-server system to serve a user’s airport lookups by using RPCs. The system consists of three components: the client, the places server and the airports server.

audiovisualization

This project demonstrates audio data exploration and analysis. See the Powerpoint for our full presentation.

dictionary-bst

global-address-rest-api

Team assignment for CPSC 5200 Architecture. This API will support three main features: adding an address, searching for an address, and searching for common addresses among countries. The addresses must be in a country-specific format.

hangman-via-network

Project assigned in CPSC 3500 Computer Networks. This was my first experience with programming over the network. We used sockets to send TCP/IP packets between the client and the server. Online leaderboard was displayed to each client following completion of their game. Score is calculated as follows: number of guesses divided by the length of the word (lower score is better).

image-to-image-generation

Repository containing example code for image-to-image generation using Amazon SageMaker and HuggingFace.

k-nearest-neighbors

Project assigned in CPSC 3400 Languages and Computation. Uses the K-Nearest neighbors algorithm to estimate a value based on values of other entities related to the entity being predicted. For example, we used known house prices to estimate the price of a new home. We used houses that were geographically nearest to the new house and their existing prices to estimate the price of that house. K value can be changed to alter the number of houses nearest the new house that were being used to predict the new house's price.

large-scale-data-preprocessing-and-machine-learning-with-adsb-flight-data

Exploration and processing of large amounts of ADS-B flight data using Apache Spark. Also includes basic ML modeling using Amazon Sagemaker.

multi-threaded-c-

Project assigned in CPSC 3500 Computer Networks. Implements multi-threaded inventory management for a store. Takes file paths containing files with each salesperson's sales for the day, and processes them simultaneously to provide total sales and restocking of the shelves in the store.

news-feed

priority-queue-heap

simple-hangman-game

Simple hangman game written in Python. Chooses a word randomly from the words.txt and challenges the user to complete the word by guessing individual letters. The user is given a maximum of 6 incorrect guesses before they lose. Each time the user enters an incorrect letter, a body part is added to the gallow. Once the entire body has been added, the user has been "hung" and they lose the game. The user wins the game by successfully guessing all the letters before they are "hung".

sms-spam-detection

Machine learning task to identify spam SMS messages. Project involves processing of noisy unstructured text and other NLP techniques.

spotify-song-data-analysis-and-modeling

Exploratory data analysis and preliminary modeling of Spotify song dataset.

sql-parser

fork of hyrise/sql-parser

student-performance-prediction

Machine learning task to predict grades of students based on demographic information. Dataset taken from UCI Machine Learning Repository. Includes both local and cloud implementations.

us-businesses-data-exploration-and-analysis

Taking data from 3 different sources, evaluating the distribution of businesses in various sectors across the United States.

water-quality-analysis-and-prediction

Data analysis and prediction using a water quality dataset. Developed using various Amazon Sagemaker capabilities. See README for more details.

wordladder

Project assigned in CPSC 3400 Languages and Computation. We were given two files: dictionary.txt contained a list of all the valid words in the English language and pairs.txt is where the client would insert pairs of words to find solutions for. Word Ladder program finds shortest path between pairs of words, differing the word by only one letter each step. Words in pairs must be of the same length but any length is supported as long as both words in that particular pair are the same length.