Machine Learning

What is supervised learning?

• Training a model on a labelled dataset.

• Finding patterns in unlabeled data.

• Maximizing rewards through actions.

• Grouping similar items without labels.

What is the goal of supervised learning?

• To discover hidden patterns.

• To learn a mapping from inputs to outputs.

• To maximize cumulative rewards.

• To group similar items.

What does unsupervised learning deal with?

• Data with labelled responses.

• Data without labelled responses.

• Data that is always structured.

• Data that is always numerical.

What is the goal of unsupervised learning?

• To learn the best strategy.

• To discover hidden patterns.

• To predict outcomes.

• To maximize rewards.

What is reinforcement learning?

• Training an agent to make decisions.

• Finding patterns in data.

• Grouping similar items.

• Learning from labelled data.

What is the goal of reinforcement learning?

• To learn the best strategy to achieve the highest reward.

• To group similar items.

• To predict outcomes.

• To discover hidden patterns.

What type of data does semi-supervised learning utilize?

• Only labelled data.

• Only unlabelled data.

• A combination of labelled and unlabelled data.

• Data that is always structured.

What is the primary difference between supervised and unsupervised learning?

• Supervised learning uses labelled data, while unsupervised does not.

• Unsupervised learning is faster than supervised learning.

• Supervised learning is only for classification tasks.

• Unsupervised learning requires more data than supervised learning.

Which of the following is a common application of reinforcement learning?

• Image classification.

• Game playing.

• Data clustering.

• Text generation.

What is the purpose of a reward function in reinforcement learning?

• To evaluate the performance of an agent.

• To provide feedback to the agent based on its actions.

• To classify data into different categories.

• To optimize the learning rate of the model.