A variety of classification models made with Keras, mostly for the Fall 2023 Open Project, Hosted by the Wat.ai Design Team from UWaterloo. All models try to classify images from the Stanford Online Products Dataset (https://www.tensorflow.org/datasets/catalog/stanford_online_products).
Ultimately, I got 1st place for the Classical ML model for Binary Classification and 2nd place for the Deep Learning Multiclass model (10 types of products).
Each folder contains different attempts at creating models to get the highest possible score at the task at hand, using different classification techniques. The task is further described within the README in each folder.
We also have my submission for the CxC hackathon, hosted by UWaterloo's Data Science Club. I completed the Challange hosted by Infinite Investments, where we had to create a binary classifier to figure out if a customer will "churn" or not based off of different characteristics of the data. Full details of the challange are listed in the official documentation (https://docs.google.com/document/d/1poZbgbxUnFX_08TkuMe57qEKOEfasiP_IrGN82o2tr8/edit?usp=sharing).