COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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training a computer to recognize specific data
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all the data collected
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measure the accuracy of your model, create the model
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Give an expected result.
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Detailed explanation-1: -Pattern recognition is a derivative of machine learning that uses data analysis to recognize incoming patterns and regularities. This data can be anything from text and images to sounds or other definable qualities. The technique can quickly and accurately recognize partially hidden patterns even in unfamiliar objects.
Detailed explanation-2: -The trained and tested model developed for recognizing patterns using machine learning algorithms is called a classifier. This classifier is used to make predictions for unseen data/objects.
Detailed explanation-3: -Training data is the initial dataset you use to teach a machine learning application to recognize patterns or perform to your criteria, while testing or validation data is used to evaluate your model’s accuracy. You’ll need a new dataset to validate the model because it already “knows” the training data.
Detailed explanation-4: -To achieve image recognition, machine vision artificial intelligence models are fed with pre-labeled data to teach them to recognize images they’ve never seen before.