This volume explores a diverse range of applications for automated Machine Learning and predictive analytics. The content provides use cases for Machine Learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. The major objective of Smart Electronic Systems is to provide a platform where researchers from the fields of hardware and software may work together under one roof to speed up the development of smart electronic systems. Effective and secure data sensing, storage, and processing are essential in today's information age. Modern smart electronic systems meet the criteria of effective sensing, storage, and processing. Effective techniques and software that allow for a quicker analysis and retrieval of necessary data are simultaneously becoming more important. The internet world now includes big data, which comprises large, complex data collections. It is becoming harder to store and analyse the vast amount of structured and unstructured data that has to be collected. With concurrent hardware and software development, the Internet of Things (IoT) and cyber-physical systems (CPS) have been growing to include everyday consumer electronics. The effectiveness and performance of current and next generations of computing and information processing systems depend on advancements in both hardware and software. Some of the focused areas in this field include memristor and memristive systems, advanced 3D IC technologies, design methodologies, and 3D pacing. Others include molecular electronics, biosensors, bio-molecular and biologically inspired computing, nanoelectronics for energy harvesting, spintronics, domain-wall and phase-change memories, and nanoelectronics for energy harvesting.