In the last couple of years we have witnessed an enormous increase of machine learning
(ML) applications. More and more program functions are no longer written in code, but learnt …

The influence of machine learning (ML) and application of artificial intelligence (AI) on the
healthcare sector is examined in this study. This study examined numerous actual instances …

Dataset licensing is currently an issue in the development of machine learning systems. And
in the development of machine learning systems, the most widely used are publicly …

The development of Machine Learning (ML) based systems is complex and requires
multidisciplinary teams with diverse skill sets. This may lead to communication issues or …

The complexity required in the software development of machine learning (ML) applications
introduces additional challenges to requirement engineering (RE) activities. RE researchers …

The surge in data availability and processing power has made it possible for Artificial
Intelligence (AI) to advance at a faster rate. However, the different nature of AI systems has …

ABSTRACT [Context] Engineering Artificial Intelligence (AI) software is a relatively new area
with many challenges, unknowns, and limited proven best practices. Big companies such as …

Machine learning and software development share processes and methodologies for
reliably delivering products to customers. This work proposes the use of a new teaming …

The presence of bugs in a software release has become inevitable. The loss incurred by a
company due to the presence of bugs in a software release is phenomenal. Modern …

Artificial Intelligence (AI) has emerged as a buzzword for current software applications. The
modern advancements in the Information Technology sector have invigorated the need to …