Hand-written Digit Recognition using Convolutional Neural Network in Python with Tensorflow

Abstract

Recently, deep learning has transformed machine learning by significantly enhancing its artificial intelligence as Artificial Neural Networks (ANN) have become increasingly prevalent. Due of its extensive range of applications in fields such as intelligence, healthcare, medical, athletics, robots, etc., Machine learning algorithms is remarkably used in a wide range of industries. At the core of incredible advancements in deep learning are convolutional neural networks (CNN), which integrate artificial neural networks (ANN) and contemporary deep learning algorithms. Across a variety of applications, including pattern classification, phrase classification, voice recognition, image identification, text summarization, documentary analysis, scene recognition, and handwritten digit recognition, it has been used. Our research's objective is to develop a model that can accurately compare image comparisons and identify handwritten numbers. We used the Modified National Institute of Standards and Technology (MNIST) dataset to conduct our experiment CNN.