Web Design
Happy Mutts
2022
Happy Mutts needed an online store designed with full e-commerce capabilities.
Related Work
Happy Mutts
Happy Mutts needed an online store designed with full e-commerce capabilities.

Sunny's
Sunny's Babysitting Services needed a fully functional website designed to provide information to clients and to serve as the main point for booking services.

Release and Unleash
Release and Unleash needed an overhaul of their outdated website. The team redesigned and developed a multi-page e-commerce site with a orimary goal of telling the story of Release and Unleash and providing an online store where customers can find their products.

D3 Trucking
D3 Trucking needed a website designed to help with the application process, booking consultations, and selling their digital booklets.

Crypto Analysis
Unsupervised Machine Learning: Clustering


Credit Risk Analysis
The Easy Ensemble AdaBoost Classifier was best at predicting high risk credit applications in comparison to the other models. With a 0.925 accuracy and a 0.91 recall score, both Easy Ensemble AdaBoost and Random Forest Classifiers outperformed the Resampling techniques in accurately predicting high-risk credit card applicants.

Neural Network and Deep Learning
Overall results of the deep learning classification problem was 73% accuracy.
