Machine Learning 2020
Guide to Understant Big Data Analytics
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ナレーター:
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Cass Merry
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著者:
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Myles Bellisario
このコンテンツについて
Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves.
The way toward learning starts with perceptions or data - for example, models, direct understanding, or guidance, so as to search for designs in data and settle on better choices later, depending on the models that we give. The essential aim is to permit the computers to adapt naturally, without human intercession or help and modify activities appropriately.
Another definition is that machine learning is the study of getting computers to learn and act like humans do and improve their learning after some time in independent style, by sustaining them with data and information.
Machine learning is a principal subdivision of artificial intelligence. It is the study of getting computers to learn and act like humans do and improve their learning after some time in independent style, by sustaining them with data and information. At that point, when presented with new data, these computer programs are empowered to learn, change, create, and develop without anyone else's input.
©2019 Mattia Pasquale (P)2020 Mattia Pasquale