Digit Recognition of MNIST Handwritten Using Convolutional Neural Networks (CNN)

One of the very significant problems in pattern recognition applications is the recognition of handwritten characters. The applications of digit acknowledgement include postal mail organization, bank actual check processing, structure information transmission, and others. The capacity to create an effective algorithm that can detect handwritten digits given by users via a scanner, tablet, and other digital devices is at the core of the issue. The method for offline handwritten digit recognition presented in this work is based on various machine learning techniques. In view of various AI techniques, this work proposes a mechanism for detaching manually written digit acknowledgement. The handwritten digit analyzed with accuracy and based on error rate so that user is able to read the digits very effectively. Model has been used to analyze un the form of data loss. Proposed technique more useful to unrelated handwritten data to related data. This paper's main goal is to ensure effective and reliable methods for identifying transcribed digits.