Detection of Covid 19/ Pneumonia by using Machine Learning Techniques

Millions of individuals worldwide were infected by the pandemic illness known as COVID 19. On the other hand, pneumonia is a condition that results in a lung infection that causes the air sacs to enlarge, making breathing difficult and occasionally fatal. As a result, the Kaggle data repository is where the CT pictures of both pneumonia and the COVID 19 are found. The widespread demands for diagnosis caused by the COVID-19 and pneumonia have given rise to the development of more sophisticated, quick to react, and effective detection techniques. An image processing-optimized convolution neutral network model is created using machine learning techniques with the aid of Google Colab software. Kaggle provided 5425 photos for use. Using the CT scan and X-rays pictures as dataset, a straight forward convolution neural network (CNN) and modified Alex Net model are implemented. The experiments' findings indicate that the models in use can deliver accuracy of up to 90%. This highly effective method of identifying both diseases cuts down on time significantly and prepares the path for a sophisticated diagnosis system