Projects

Check out some of my projects below, check my GitHub for everything

Pokedex Website

Description:

A Pokemon Website that displays more than 890+ Pokemon from the video games and anime. The information displayed would be name, typing, location, moveset, etc.

Technologies:

JavaScript, HTML, CSS, MongoDB, Express

Repo

National Dex

Description:

A Pokemon Encyclopedia that displays more than 890+ Pokemon from the video games and anime. The information displayed would be name, typing, location, moveset, etc.

Technologies:

QT and C++

Question Answering Chatbot

Description:

I participated in the Summer Transportation Internship for Diverse Groups(STIPDG) where I got to work at the U.S. DOT Volpe National Transportation Systems Center. Under my mentor, using AI and NLP, I created a Closed Domain Question Answering Chatbot that can be hosted on either a website or as a standalone desktop application.

Technologies:

AI, Natural Language Processing, Python, Tkinter

Tower Defense Unity

Description:

This game emulates a tower defense game using Unity. All code is written entirely in C#. This was created from a tutorial that I followed by Brackeys on Youtube from his series "Tower Defense".

Technologies:

C#, Unity3D

Tic Tac Toe - Python

Description:

For my software engineer college course, my group and I decided to make a Python version of Tic Tac Toe as our class project.

Technologies:

Python, Pygame

Ringer: Smart Doorbell

Description:

This was a project that I created with a partner for a summer program at UCI called Inspire in which we had to create a smart doorbell using a Raspberry Pi.

Technologies:

Python, Raspberry Pi, Solid Works

MNIST-Classification

Description:

The purpose of the program that I wrote was to clearly present metrics about the classifications about either of the MNIST datasets. The user is able to run metrics on Classifiers in Python like RandomForestClassifier, KNeighborsclassifier, etc in order to see how well it performs. The output is printed to an excel spreadsheet and a csv file for the user to compare the different metrics. These metrics include Accuaracy, F1-Score, Precision Score, Recall Score, Training Time, non-default parameters(if any were changed), a picture of the Confusion Matrix, and a full Classification Report.

Technologies:

Python