Handwritten Digit Recognition using Machine Learning with Python

Handwritten Digit Recognition is one of the essentially significant issues in pattern recognition applications. The main purpose of this project is to build an automatic handwritten digit recognition method for the recognition of handwritten digit strings. This paper proposes a simple convolution neural network approach to handwritten digit recognition. Convolutional Neural Network model is implemented using MNIST dataset. This dataset consists 60,000 small square 28×28pixel grayscale images of handwritten single digits between 0 and 9. The applications of digit recognition include postal mail sorting, check processing, form data entry, etc. The core of the issue exists in the capacity to foster a proficient calculation that can perceive manually written digits and which is put together by clients by the method of a scanner, tablet, and other computerized gadgets.