Jordan's Projects
Daily coding challenge
Andy is a multifunctional robot capable of facial recognition, obstacle avoidance, and balancing with only two wheels. He has a unique design, created with Fusion 360 so that it can be 3D printed.
Asteroids game made with p5.js (javascript library).
Uses LDA topic modelling and the Jensen Shannon similarity formula to find content based book suggestions.
Simple color wheel that gets the rgb and hex values of the color that the mouse is currently on. It also gives similar color results.
This project sought to find an accurate sentiment analysis model for Ben & Jerry's ice cream reviews using machine learning classification. I created a dynamic web based platform to accept new reviews and classify them in real time. This platform also allows for user feedback and a continuously improving model.
Application that uses machine learning to recognize user's emotion and then suggest a playlist for them.
Machine learning classifier to determine if exoplanets identified by NASA are likely to be habitable.
Game and machine learning implementation of Flappy Bird.
Generated web designs using a dynamic genetic algorithm approach.
This machine learning project uses sentiment analysis to determine whether a Ben & Jerry's ice cream review is positive or negative.
Uses deep learning to add colors to black and white photographs.
An app for the productive student!
Boggle game implementation using Python.
Movie app allowing users to search for movies and add them to either their watchlist or favorites list. Includes movie posters, descriptions, and a few facts about the films.
3D Rubix Cube.
Accurate simulation of planets in solar system.
Style transfer between famous art styles and an image of choice using machine learning and a premade model from Google Magenta.
I took data with an Arduino Uno and an acelerometer/gyroscope sensor in order to train a machine learning model to classify whether the controller is being moved up, down, left, or right. I compared several different models to determine which one performed the best. I found that the Support Vector Machine was most suited for the project and it obtained about an 86% accuracy. The model could be uploaded to another microcontroller to be used as an HID device with programs such as Fusion 360 or Photoshop.
Introduces a new loss function for image colorization that prioritizes saturation over hue in an effort to decrease the effect of ambiguity and to produce vibrant and colorful images.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent