Trained a state-of-the-art Deep Convolutional Neural Network for the Street View House Numbers (SVHN) dataset, accurately classifying 600000 real-world digit images with an accuracy of 87.5%.
Created visualization layers to showcase the relationship between input variables and trained model’s predictions, increasing interpretability & providing additional insight into predicted labels with 90% certainty.