1. What is Machine Learning?

A) A field of study that gives computers the ability to learn without being explicitly programmed. B) A way to explicitly program computers to perform specific tasks. C) A field of study focused on hardware engineering. D) None of the above

2. Which of the following is an application of Machine Learning?

A) Autonomous vehicles B) Email spam filtering C) Recommendation systems D) All of the above

3. In Machine Learning, what does "Training" refer to?

A) Adjusting parameters of a model to fit data. B) Setting up a test environment for model evaluation. C) Gathering a large dataset for model testing. D) Training a neural network using labeled data only.

4. Which of the following is a type of Machine Learning system?

A) Supervised Learning B) Reinforcement Learning C) Unsupervised Learning D) All of the above

5. What is a feature in Machine Learning?

A) A characteristic or attribute of the data. B) A label used to classify data. C) The accuracy score of a model. D) None of the above

6. What is an instance in Machine Learning?

A) An individual example or data point. B) A feature used in a dataset. C) A model parameter. D) A category or label.

7. What is labeled data?

A) Data without any identified output. B) Data that has an associated output or label. C) Data that is ready for testing. D) Data that only exists in a supervised learning system.

8. What type of Machine Learning system continuously learns from incoming data?

A) Batch learning B) Online learning C) Semi-supervised learning D) Active learning

9. What does generalization mean in Machine Learning?

A) The ability of a model to perform well on new data. B) The process of creating an exact model copy. C) Reducing the model's complexity. D) Training the model on the test dataset.

10. Which of the following describes unsupervised learning?

A) Learning from labeled data. B) Discovering patterns from unlabeled data. C) Only used in reinforcement learning. D) Used in supervised learning systems.