An Intelligent Way to Recognize Digits using Convolutional Neural Networks (CNN) Algorithm

The Handwritten digit recognition issue in pattern recognition systems is one of the more significant technical issues. Applications for digit recognition include data entry forms, bank check processing, postal mail sorting, and more. The capacity to create a practical algorithm that can recognize handwritten digits given by users via a scanner,tablet and other digital devices is at the core of the issue. The study's main goals were to create a machine learning algorithm and an optimization technique to improve the precision of handwritten digits recognition, as well as to analyze the performance of the proposed algorithm with test data set. This model offers a method for recognizing handwritten digits offline that is based on various machine learning techniques. There are several machine learning algorithms such as Support Vector Machine, Random Forest, Multilayer Perceptron, Convolutional Neural Network etc. In this project is aimed to use Convolutional Neural Network to complete the task. The MNIST dataset also used in this project. The main objective of this model is to ensure effective and reliable approaches for recognition of handwritten digits.