Abstract
Machine learning is a particular branch of artificial intelligence that teaches a machine how to learn, whereas artificial intelligence (AI) is the general science that aims to emulate human abilities. An AI method called machine learning teaches computers to learn from their past experiences. Machine learning algorithms don't rely on a predetermined equation as a model, but instead "learn" information directly from data using computational techniques. As the quantity of learning examples increases, the algorithms adaptively get better at what they do. This paper provides an overview of the field as well as a variety of machine learning approaches, including supervised, unsupervised, and reinforcement learning and various languages used for machine learning.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Science and Research Archive
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
