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In addition to spam detection, social media websites are using ML as a way to identify and filter abuse.
But no education system in the world can afford a tutor for every child, so this is where AI might be able to step in.
Artificial tutors, made to look and sound as much like humans as possible, could take the lead in delivering personalised education.
Inaccuracy and duplication of data are major business problems for an organization wanting to automate its processes.
Machines learning (ML) algorithms and predictive modelling algorithms can significantly improve the situation.
Four years ago, email service providers used pre-existing rule-based techniques to remove spam.
But now the spam filters create new rules themselves using ML.
For example, a recent ground-breaking discovery on the disease Amyotrophic Lateral Sclerosis (ALS), was made through a partnership between Barrow Neurological Institute and the artificial intelligence company IBM Watson Health.
IBM Watson, the artificial intelligence computer, reviewed thousands of pieces of research and was able to identify new genes linked to ALS.
Unsupervised learning along with location detail is used by Facebook to recommend users to connect with others users.
Machine Learning in the medical field will improve patient’s health with minimum costs.