Paper Title
Detecting Pneumonia using Machine Learning

Abstract
Throughout its evolution, artificial intelligence has found applications in a variety of sectors, particularly in recent years as the amount of data available has increased dramatically. Its main goal is to help people make better, faster, and more accurate judgments. Machine learning and artificial intelligence are rapidly being used in medicine. This is especially true in medical areas that use a variety of biomedical images and rely on gathering and analysing a large number of digital images for diagnostic processes. Machine learning in medical image processing aids consistency and improves reporting accuracy. This research explains how machine learning techniques are used to analyse chest X-ray pictures to aid in the diagnosing process. To create a processing model, the research focuses on the application of a deep transfer learning technique based on a convolutional neural network. This model is tasked with assisting with a classification problem that entails determining whether or not a chest X-ray displays alterations associated with pneumonia and categorising the X-ray pictures into two groups based on the detection results. Keywords - Convolution Neural Network, Deep Transfer Learning, Machine Learning