Graph Algorithm Visualizer

I've always been interested in pathfinding after learning about the topic in an A.I course I enrolled in as an undergraduate. Many of the video games that I play use pathfinding, which pushed me towards the development of this pathfinding application. This pathfinding application helps users visualize pathfinding algorithms.

This is an undergraduate group project, and was my first "large" group project. Our team was tasked with the development of an application similar to Google Docs. Users create an account, and through the account, the user is able to create, edit, and share documents with other users. Our team developed a locking feature, which prevents multiple users from editing and saving the same document. Users can make their documents private, preventing other users from editing. The application also gives the user the ability to grant permissions to other users to edit their documents. Users do not have to make an account; such users will be labeled as visitors. Visitors are limited to only having the ability to view public documents. The application also has a taboo word detection function, which prevents users from using "taboo words" in their documents, and its own version control system, which lets users revert back to older documents.

This is an undergraduate team project, which showcases our relational databases knowledge. At the time, I figured the best way to showcase our knowledge was to do a social media website, which my team was in full agreement with. The purpose of this website is for users to find other users who play similar games. Each user has their own profile, from which the user has the ability to list the video games that they play. The website also has a friends list feature. However, most of the features here are hard coded. (There is no user authentication, You login as simply "John").

This is an undergraduate school project that showcases my knowledge of inheritance and polymorphism. The objective is to simulate the perfect environment of carnivores, herbivores, and plants. Carnivores would eat the herbivores, and the herbivores would eat the plants. Each agent can age, reproduce, eat, and die. Each loop would be counted as a day. Carnivores, and herbivores would hunt for food with a view distance determined randomly. Reproduction was determined by how much food the agent had consumed and how healthy it was. The baby had a 50/50 chance of being male or female. This was one of the first projects that was assigned to me during my undergraduate studies. I quite enjoyed this project, and many of my classmates who I talked to about it enjoyed it as well.

A web application using the Python Django web framework. Users can create accounts, log on, and create works of fiction. Other users can comment on the stories, and the author has the ability to make their works of fiction private.

As a frequent window shopper, I wanted to make an Android application which documents the interesting finds that I would encounter while exploring the local mall with my family and friends. Once the user finds an article of clothing or an item that they like, the user can use the application on their phone to take an image of the item and enter relevant information about the item in the provided fields. These fields include the size, color, brand, kind of item (shirt, hat, pants, etc), price, and most importantly the location of the item. The description and picture of the item is saved and can be reassessed on the application, which allows the user to trace back their location to where they last saw that item for as long as the app is installed on the phone (hopefully the store still has it in stock).

After taking an A.I course in City College I became very interested in pathfinding algorithms and search algorithms. I decided my next project after my Algorithm Visualizer would be a N x N Tic Tac Toe game where users can play against different algorithms. This project shows users different algorithms, how it behaves, intelligence, and the speed. I gave the user some power also, the user can modify the size of the board, and max depth for minimax. Algorithms I implmented are Depth First Search (Very Slow), Depth First Shortest Path (Very Slow), Minimax (Time Complexity depends on depth), and Minimax with Pruning (Time Complexity depends on depth).