Web-based application that creates battery cycle data visualizations
Compatible with Neware and Arbin software-generated data
Used Python, Matplotlib, Pandas, and Streamlit components to compile and visualize data
Utilized by University of California, San Diego battery labs to help analyze their data easily
Source code can be viewed in this repository
Group project completed as part of COGS 108: Data Science in Practice
Data science project that analyzes the relationship between DeviantArt content popularity and the keywords contained in their captions
Used Python, Jupyter Notebook, DevinatArt API, and Git to help analyze data and program
Data visualization from MatPlotLib and NumPy used to show the rankings and counts of common content popularity
Trained machine learning models such as Decision Tree Regressors, OLS, and Linear Regressors to predict the popularity of content based on keywords
Pair programmed a Machine Learning App for SPIS 2021
Accesses + generates user playlists based on astrological sign and favorite music genre
Used peer data as training models for app
Data visualization used to determine popularity of genres among common astrological signs
Utilized Spotify API (via Spotipy), Local Hosting, Python, and Git
Programmed in Visual Studio Code and GitHub
Programmed for IB HL Computer Science 2021 IA
Computer application dedicated to helping the user keep track of tasks they needed to complete with real-time updating
Used real-time dates (shown with MM/DD/YYYY) and time (shown with HH:MM:SS)
Utilized EasyApp Java extensions and coded in Java
Programmed in NetBeans