Projects
Below are a few of my proudest projects. I've got some more in the works and plenty of exciting plans for the future, so stay tuned for updates. Feel free to check out my GitHub for even more cool stuff!
ZoomMate
ZoomMate is a program I created that fully automates the process of attending Zoom meetings. It allows users to input their meeting details such as start times, end times, Zoom links and days active into a master json file. I used python’s webbrowser library to open the Zoom meetings with the links at the specified start times, automatically joining the meetings. To exit the meeting once they conclude, the Zoom application is killed. ZoomMate is able to handle multiple meetings occurring on different days throughout the week as it references the days that the meeting is active before attending each one.
Source Code
Fruity Facts
This was a creative collaboration between a group of friends that uses machine learning (ML) techniques. By simply providing an image of a fruit, Fruity Facts harnesses a trained ML model built on the TensorFlow framework to identify the given fruit. We trained the ML model on tens of thousands of fruit images, fine-tuning it through seven iterations. As a result the model was successfully built with an accuracy rate of 99.8%. The program then calls the Edamam API, enabling users to access comprehensive nutritional information for the identified fruit. It displays the exact composition, vitamins, minerals, and other essential nutrients with a single click.
Source Code
SiteSight Insights
This program uses the sqlite3 Python library, this tool queries the user’s local browser database, extracting tons of information. This includes records of every website the user has visited, along with the corresponding date and time of each visit, as well as the duration spent on each site. The program then parses through the URLs and calculates the frequency of each domain, generating comprehensive visit counts. The program can then display the results in a textual format, or in a graphical format. It uses Python’s matplotlib module to graph the user’s top 10 most frequently visited websites.
Source Code