12Software Engineering in Machine Learning Applications: A Comprehensive Study
Kuldeep Vayadande1*, Komal Sunil Munde2, Amol A. Bhosle2, Aparna R. Sawant1 and Ashutosh M. Kulkarni1
1Vishwakarma Institute of Technology, Pune, Maharashtra, India
2MIT Art, Design and Technology University, Pune, Maharashtra, India
Abstract
The research of developing complex algorithms whose accuracy increases over time is known as machine learning. To solve the problem of generating and dealing with large, powerful computers in a quickly changing and dynamic environment, machine learning approaches have become more important in many computers’ maintenance and advancement tasks. Machines’ intelligence strategies have been shown to be extremely applicable across a wide range of industries. It is not unexpected that many tasks that go into the creation and upkeep of technology may well be rethought as knowledge difficulties and accosted in terms of comprehending processes. Over the past 20 years, interest in using machine learning algorithms in software design has increased, along with some positive publications and results. In this paper, we have conducted a review of prior research on machine learning approaches and provided a broad overview, including benefits and drawbacks and a comparison of a few existing algorithms. This paper presented a selection of the most current revelations in this new market niche.
Keywords: Machine learning, machine intelligence, supervised, unsupervised, software ...
Get How Machine Learning is Innovating Today's World now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.