Abhijeet Prajapati

Our semester-long course project resulted in the development of a fast and responsive website for the Niagara-on-the-Lake Museum. This website serves as an immersive digital showcase for all museum exhibits, providing visitors with accurate information about each display. Key features include a scheduling system that enables visitors to plan their museum visit conveniently. Additionally, an admin page allows museum staff to update exhibit information, which is stored in Supabase, seamlessly. Notably, our project received recognition from our professor, who proposed its adoption by the actual museum.

Our project focused on creating a deep learning model using the Keras library to classify handwritten digits from the MNIST dataset. Our model achieved an accuracy of 98% during training. Users can easily interact and test the model with the GUI, drawing digits for accurate recognition by the trained model.

Simple terrain generation program created in JavaScript with the p5.js library. It utilizes Perlin noise to create landscapes, distinguishing water, land, grass, trees, and mountains with varying colors. The gradient in colors indicates height changes within each terrain type. Users can adjust the seed, zoom in/out, and save the terrain as a .png file.