This is a web-based Word Search 1v1 lockout game, where you try to find more words than your opponent on the same board.

You can create your own room, and easily invite your friends by sending them the room code, or by sharing a URL that will automatically connect them to your room.

The host can also adjust some game settings as well, such as the board size and the number of hidden words.

Each player can also choose their own font preference for the game board.

I wanted to learn about Golang, as well as real-time data sharing via WebSockets, so I decided to make this game.

I have a server deployed, so you can play my game right now!

This word game was inspired by WORDLE.

My girlfriend and I had a rotation of daily word games we would play, and I wanted to make my own to add to our mix.

The objective of the game is to guess the secret word. The game will give you hints, in the form of definitions and synonyms, to allow you to formulate your guess. You are allowed up to 5 guesses before you lose.

To accumulate the word data needed for this game, I wrote a python script that would fetch word data from a dictionary API. I fed the script a massive list of 5 letter words, and filtered out the words that didn't have enough definitons or synonyms.

You can play this game yourself right on my website!

As a final project, I made a Convolutional Neural Network (CNN) using only NumPy to classify the MNIST handwritten digits dataset.

Before this project, I had a very high level understanding of the CNN architecture, but having to code it from the ground up gave me a much deeper grasp on them.

This project includes code for training CNN's, as well as code for running trained models against the test set. It also includes a small drawing program that lets you write your own digits, and have them be classified by a trained model.

The GitHub repo includes six models trained with different hyperparameters and layer configurations. The test set acccuracy of these models range from 96-98%.

This project was completed in collaboration with two other students.

A platform for organizing gift giving and group events.

When you are buying gifts for friends or family, you have to make sure no one else is getting them the same thing. This can be a cumbersome task with large groups, so Wishify was created to solve this problem.

You can create Wishlists with your most wanted items, and easily share them. Others can view your Wishlist and mark off items, showing other people what they plan to purchase. You can manage who can see the Wishlist contributions, and who is blind to them.

You can also create Events, which are used to manage groups of Wishlists. Wishify can be used for coordinating Christmas gifts, potlucks or even camping trips.

This was a course project I made as a part of a six student team.

This is an Android navigation app for Brock University's most confusing building, the Mackenzie Chown Complex.

This building can be very confusing to navigate, and it is very easy to get lost, especially for visitors and new students. This app aims to solve this issue.

The app is written in Java and makes use of the ArcGIS Runtime API for Android.

A PDF map of the building was georeferenced for use as the basemap.

This was created in collaboration with another student as a course project.

This project allowed me to explore programming in the Android environment. It was an assignment in my Mobile Computing class at Brock University, where we had to create a calculator app using Android Studio.

This calculator has 2 modes, Basic Mode and Formula Mode.

Basic Mode allows you to perform simple calculations one after another. Similar to the Apple calculator found on their mobile devices.

Formula Mode allows you to enter an entire expression at once, with potential parentheses, and have it evaluated.

To evaluate formulas, the app converts the entered infix expression into postfix notation, and then evaluates the postfix expresion.