Machine Learning and Deep Learning: A Comprehensive Overview

Machine Learning (ML) and Deep Learning (DL) are two core areas of Artificial Intelligence (AI) that have significantly transformed technology and research. Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today’s Fourth Industrial Revolution (4IR or Industry 4.0). Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various application areas like healthcare, visual recognition, text analytics, cyber security, and many more. However, building an appropriate DL model is a challenging task, due to the dynamic nature and variations in real-world problems and data. Moreover, the lack of core understanding turns DL methods into blackbox machines that hamper development at the standard level. This paper presents a comprehensive overview of ML and DL, their theoretical foundations, methodologies, applications, and current trends. The paper aims to clarify the distinctions and synergies between ML and DL and provide insights into their practical implications in various domains