This report aims to explore multiclass image classification problems, specifically using the MNIST dataset. Following François Chollet's universal workflow from "Deep Learning with Python," we strive for a systematic approach to develop, evaluate, and refine our model.
This report aims to explore multiclass image classification problems, specifically using the MNIST dataset. Following François Chollet's universal workflow from "Deep Learning with Python," we strive for a systematic approach to develop, evaluate, and refine our model.
This report aims to explore multiclass image classification problems, specifically using the MNIST dataset. Following François Chollet's universal workflow from "Deep Learning with Python," we strive for a systematic approach to develop, evaluate, and refine our model.