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Joined: September 17th, 2020, 8:42 pm


Post by kmanzoor » September 17th, 2020, 9:41 pm

The classical definitions is that it is the theory of algorithms that infer the functions they compute from example data . An illustration of this is the " Science of the Learning " paper which is presumably the seminal good learning title . In this frame it is supposed to be system Science ' s solution to philosophy.

This This is probably too narrow now , as the ideas of inferencing a product from instances make the most sense with classification or regression problem and make less work with factor or other questions .

Historically , machines learning was something of a revolution within artificial Intelligence , . AI focus much on logical though than calculus or Statistics , and prefers he {} and Search to formal programming . It was a a pretty open topic search program in which it is very harder to judge progress . The prevalence of machines learning in a university was maybe due to the want of successes and increasing s {} {} people had of AI research in the Late 90s . machine learning is , in addition , an ultra well developed field focuses on concrete algorithm {} and mathematical problems . Focus focusing on better specified issues with concrete measure of success really aided researchers insulate themselves from the discouragement with AI generally ( and variety of funds ).

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