A Machine Learning system predicts from historical data, builds the prediction models, and whenever it receives new data, predicts the output for it. The accuracy in expected production depends upon the amount of data, as the massive amount of data helped to build a better model which predicts the output more accurately.
Applications of machine learning
Image recognition is one of the most popular applications of machine learning. It is used to identify objects, places, persons, digital images, etc. For these images, the measurement narrates the output of every pixel in a snap. Face recognition is also one of the best characteristics that have been advanced by machine learning only. It helps to acknowledge the face and send notifications related to that to people.
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The famous use case of face detection and image recognition is, Involuntary friend tagging suggestion:
Facebook offers us a feature of auto friend tagging suggestions. Whenever we upload photos with our Facebook friends, we automatically get a tagging suggestion with a name. The technology’s backside is machine learning’s face detection and recognition algorithm.
It is the basis of the Facebook project “Deep Face,” which is responsible for face recognition and person identification in the picture.
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Conclusion
Machine learning is a quickly rising domain in computer science. It has applications in almost every other field of study. It is already being implemented commercially because machine learning can solve problems that are too difficult or time-consuming for humans to solve.
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