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.
Cite
CITATION STYLE
Shaveta. (2023). A review on machine learning. International Journal of Science and Research Archive, 9(1), 281–285. https://doi.org/10.30574/ijsra.2023.9.1.0410
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