A Level - Machine Learning Quiz

What is supervised learning?

• Supervised learning is a type of machine learning where the model is trained on a labeled dataset, and then makes predictions based on that training.

• Supervised learning is a type of machine learning where the model is trained on a dataset with random labels

• Supervised learning is a type of machine learning where the model makes predictions without any training

• Supervised learning is a type of machine learning where the model is trained on an unlabeled dataset

Give an example of supervised learning.

• Identifying the breed of a dog in a picture

• Predicting the stock market using historical data

• Sorting photos into albums based on facial recognition

• One example of supervised learning is the classification of emails as spam or not spam using a spam filter.

What is unsupervised learning?

• Unsupervised learning is a type of machine learning where the model does not learn patterns or relationships

• Unsupervised learning is a type of machine learning where the model is trained on labeled data

• Unsupervised learning is a type of machine learning where the model is trained on unlabeled data, allowing the algorithm to learn patterns and relationships on its own.

• Unsupervised learning is a type of machine learning where the model is only trained on images

Explain the concept of reward in reinforcement learning.

• A reward is a punishment for the agent's poor performance.

• A reward is a scalar feedback signal that indicates how well an agent is performing a given task.

• A reward is a random value assigned to the agent.

• A reward is not important in reinforcement learning.

Discuss the real-world applications of reinforcement learning.

• Reinforcement learning is only applicable in the field of fashion design.

• Reinforcement learning is only used in agriculture and has no other real-world applications.

• Reinforcement learning has real-world applications in fields such as robotics, gaming, finance, healthcare, and autonomous vehicles.

• Reinforcement learning is only used for cooking and has no other practical uses.

Explain the concept of clustering in unsupervised learning.

• Clustering is a technique in unsupervised learning where the model is trained on labeled data

• Clustering is a technique in unsupervised learning where the model is trained on unlabeled data, allowing the algorithm to group similar data points together

• Clustering is a technique in unsupervised learning where the model is only trained on images

• Clustering is a technique in unsupervised learning where the model does not learn any patterns or relationships

What is the role of an agent in reinforcement learning?

• An agent is a software program not involved in reinforcement learning

• An agent is a person who supervises the learning process in reinforcement learning

• An agent is a software program or entity that interacts with the environment and takes actions to achieve certain goals in reinforcement learning

• An agent is a software program and a type of reward in reinforcement learning

Provide an example of an unsupervised learning algorithm.

• K-nearest neighbors algorithm

• Linear regression algorithm

• Decision tree algorithm

• Support vector machine algorithm