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Questions and Answers
True or false: Supervised learning is used for classification problems only.
True or false: Supervised learning is used for classification problems only.
False (B)
True or false: Supervised learning can only be used for prediction.
True or false: Supervised learning can only be used for prediction.
False (B)
True or false: Supervised learning algorithms are only used for time series prediction.
True or false: Supervised learning algorithms are only used for time series prediction.
False (B)
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Study Notes
- Supervised learning is a process of an algorithm learning from a training dataset to approximate a mapping function from input to output.
- supervised learning can be broken down into two types: classification and regression.
- Classification problems are when the output variable is a category, such as “red” or “blue”. Regression problems are when the output variable is a real value, such as “dollars” or “weight”.
- There are many different supervised learning algorithms, each suited for a specific type of problem.
- supervised learning is used in a variety of applications, including recommendation and time series prediction.
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