Bernardo Gois, Francisco NauberFrancisco NauberBernardo GoisLobo Marques, Joao AlexandreJoao AlexandreLobo MarquesFong, Simon JamesSimon JamesFongLobo Marques, Joao AlexandreFong, Simon James2024-04-022024-04-022023978-3-031-30788-1https://dspace.usj.edu.mo/handle/123456789/5668This chapter describes an AUTO-ML strategy to detect COVID on chest X-rays utilizing Transfer Learning feature extraction and the AutoML TPOT framework in order to identify lung illnesses (such as COVID or pneumonia). MobileNet is a lightweight network that uses depthwise separable convolution to deepen the network while decreasing parameters and computation. AutoML is a revolutionary concept of automated machine learning (AML) that automates the process of building an ML pipeline inside a constrained computing framework. The term “AutoML” can mean a number of different things depending on context. AutoML has risen to prominence in both the business world and the academic community thanks to the ever-increasing capabilities of modern computers. Python Optimised ML Pipeline (TPOT) is a Python-based ML tool that optimizes pipeline efficiency via genetic programming. We use TPOT builds models for extracted MobileNet network features from COVID-19 image data. The f1-score of 0.79 classifies Normal, Viral Pneumonia, and Lung Opacity.enBook Section