Handwritten Digit Recognition using Convolutional Neural Networks (CNN) and Regression is an advanced application of machine learning that aims to create a robust model for accurately identifying and classifying handwritten digits. In this context, a systematic and effective approach is employed to leverage the capabilities of deep learning to recognize patterns within digital representations of handwritten numerical characters.