what is the function of ‘Supervised Learning’?

classifications, predict time series, annotate strings
speech recognition, regression
both a and b
none of above

The correct answer is: C. both a and b

Supervised learning is a type of machine learning in which the model is trained on labeled data. This means that the model is given a set of data that includes both the input data and the desired output. The model then learns to map the input data to the output data.

Supervised learning can be used for a variety of tasks, including:

  • Classification: This is the task of assigning labels to data. For example, a model might be trained to classify images of cats and dogs.
  • Regression: This is the task of predicting a continuous value. For example, a model might be trained to predict the price of a house.
  • Clustering: This is the task of grouping data points together. For example, a model might be trained to group customers into different segments based on their purchase history.
  • Time series forecasting: This is the task of predicting future values of a time series. For example, a model might be trained to predict the stock price of a company.

Supervised learning is a powerful tool that can be used to solve a variety of problems. However, it is important to note that supervised learning requires labeled data. This can be a difficult and time-consuming task.

Here is a brief explanation of each option:

  • A. classifications, predict time series, annotate strings: This option is correct. Supervised learning can be used for a variety of tasks, including classification, regression, and time series forecasting.
  • B. speech recognition, regression: This option is also correct. Supervised learning can be used for speech recognition and regression.
  • C. both a and b: This is the correct answer. Supervised learning can be used for a variety of tasks, including classification, regression, time series forecasting, speech recognition, and many others.
  • D. none of above: This option is incorrect. Supervised learning can be used for a variety of tasks, including classification, regression, time series forecasting, speech recognition, and many others.