One of the intriguing subfields of Artificial Intelligence (AI) is Machine
Learning (ML). The ability to learn without explicit programming has been referred to
as machine learning. Over the past few years, machine learning has emerged as an
important research topic in several business verticals. Big data's technological
developments have made accessing vast amounts of diverse data simple. With the help
of new hardware capabilities, this enormous volume of data may be processed quickly
and efficiently in a manageable amount of time. Therefore, Machine Learning
algorithms have proven to be the most successful at using big data to solve difficult
business challenges in almost real-time. This chapter briefly overviews some popular
machine learning approaches and their uses in mechatronics, particularly in the tool
wear prediction process for milling.
Keywords: Acoustic emission, Decision boundaries, Force, Frequency component, Machine Learning, Milling machining, Multidisciplinary, Support vector machine, Tool wear, Vibration.
