EMERGING TRENDS IN COMPUTING
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Supervised Learning
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Unsupervised Learning
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Reinforcement Learning
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None of the above
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Detailed explanation-1: -For supervised learning to work, you need a labeled set of data that the model can learn from to make correct decisions. Data labeling typically starts by asking humans to make judgments about a given piece of unlabeled data.
Detailed explanation-2: -A label is the thing we’re predicting-the y variable in simple linear regression. The label could be the future price of wheat, the kind of animal shown in a picture, the meaning of an audio clip, or just about anything.
Detailed explanation-3: -Supervised learning uses labeled training data.
Detailed explanation-4: -Supervised machine learning requires labelled input and output data during the training phase of the machine learning model lifecycle. This training data is often labelled by a data scientist in the preparation phase, before being used to train and test the model.