Machine Learning Quiz

What are the three main types of machine learning?

• Supervised, Unsupervised, and Reinforcement

• Unsupervised, Reinforcement, and Semi-supervised

• Supervised, Reinforcement, and Semi-supervised

• Supervised, Unsupervised, and Semi-supervised

What is supervised learning?

• A model that learns through trial and error

• A model that organizes data without known outputs

• A model trained with no example data

• A model trained with example data and known outputs

Why is it called supervised learning?

• Because the computer works without any supervision

• Because the model is trained with random data

• Because the model learns through trial and error

• Because the model is given the right answers during training

Which of the following is an example of supervised learning?

• Grouping users based on their viewing habits

• Predicting the weather using environmental data

• Organizing data without known outputs

• A robot arm learning to catch a ball

How does unsupervised learning differ from supervised learning?

• It organizes data without known outputs

• It requires human supervision during training

• It uses known outputs for training

• It learns through trial and error

What is an example of unsupervised learning?

• Predicting the weather

• Grouping users based on their viewing habits

• A robot arm learning to catch a ball

• Classifying animals as mammals or reptiles

What is reinforcement learning?

• A model trained with example data and known outputs

• A model that organizes data without known outputs

• A model that learns through trial and error

• A model that uses random data for training

Which of the following is an example of reinforcement learning?

• Classifying animals as mammals or reptiles

• Grouping users based on their viewing habits

• Predicting the weather using environmental data

• A robot arm learning to catch a ball

What is a good starting point for learning machine learning?

• Unsupervised learning

• Reinforcement learning

• Supervised learning

• None of the above

Why do many people start with supervised learning?

• It allows better understanding of the model and its predictions

• It requires no example data

• It organizes data without known outputs

• It learns through trial and error