A neural network that uses forward and backwards propagation learning to classify images of handwritten number into their respective categories.
![Neural Network Accuracy and Loss with a [784,150,50,32,10] neuron count.](images/indexPage/[784,150,50,32,10].png)
Welcome to my addition to the internet, thank you for joining me!
I am a recent graduate from the University of Guelph where I earned my Bachelor of Computer Science Honours with a minor in Geography.
Throughout my time at Guelph I learned everything from how to use tunneling to increase network security, to creating a neural network
to classify hand written numbers from 0 - 9. Additionally, I was part of a project that researched new ways to indentify flood risk in
New Orleans using social and physical factors.
On a more personal note, I enjoy focusing on improving my hobbies. I love to mountain bike, boulder and cook. I have worked at multiple
restaurants which ignited my interest in creating expressive, tasty and beautiful dishes I can enjoy with friends and family.
A neural network that uses forward and backwards propagation learning to classify images of handwritten number into their respective categories.
An image editor that can perform a series of transformation and manipulations upon given images.
A New Orleans flood risk map series developed with socioeconomic and physical risk factors using GIS tools and software.
