unsupervised learning
supervised learning
reinforcement learning
active learning
Answer is Wrong!
Answer is Right!
The correct answer is B. supervised learning.
Supervised learning is a type of machine learning in which a 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 is a very powerful tool that can be used to solve a wide variety of problems. For example, supervised learning can be used to classify images, predict customer churn, and recommend products.
Here is a brief explanation of each option:
- A. Unsupervised learning is a type of machine learning in which a model is trained on unlabeled data. This means that the model is given a set of data that does not include the desired output. The model then learns to find patterns in the data without any guidance.
- C. Reinforcement learning is a type of machine learning in which a model learns to take actions in an environment in order to maximize a reward. The model is not given any labeled data, but it learns from trial and error.
- D. Active learning is a type of machine learning in which a model is allowed to select the data that it is trained on. This can be useful in situations where labeled data is scarce.