Bengali.AI Handwritten Grapheme Classification Model Enhancements

Following up on our initial article where we outlined our baseline model; this article is being produced in order to further document our team's efforts competing in the Kaggle Bengali.AI Handwritten Grapheme Classification competition. In summary, our goal is to classify images of handwritten Bengali characters using a Convolutional Neural Network (CNN). Our initial steps in this process were covered in our initial article linked above. Here we document additional steps we took such as data augmentation, transfer learning, ResNet, and hyperparameter tuning in order to improve upon our baseline model. As mentioned in our last post, we wanted to use data augmentation to expand our training dataset and create a more robust model.