Lesson 3.5 Quiz Review

Machine learning is one of the most frequently used types of AI algorithms today.

• True
• False

In supervised machine learning, humans provide an AI algorithm with labeled data (so the AI can associate the data with a specific name or class).

• Yes
• No

If we were training a supervised machine learning algorithm to identify different types of balls, what might we use as labels for the different classes? (Select all correct answers.)

• Soccer Ball
• Baseball
• Trucks
• Football
• Clouds

If we were training a supervised machine learning algorithm to identify different types of farm animals what might we use as labels for the different classes? (Select all correct answers.)

• Cow
• Sheep
• Cars
• Chicken
• Pizza

How can humans supervise machine learning?

• By making sure to turn computers on and off at appropriate times
• By providing organized and labeled training data
• By telling the AI exactly what rules or criteria to use, step-by-step
• It’s not possible, all machine learning is unsupervised

Supervised machine learning can use an algorithm to sort objects into different types – 
 such as sorting marshmallows from cereal, or cats from dogs. What do we call algorithms 
 that do this?

• Recommendation algorithms
• Classification algorithms
• Colorful algorithms
• Search algorithms

If we wanted to train a machine learning algorithm to identify whether a person is sketching a happy or a sad face, what should the dataset we use contain – to make sure it is diverse?

• Both happy and sad face sketches drawn by many different types of people
• Only happy face sketches drawn by many different types of people
• Only sad face sketches drawn by many different types of people
• Music about people with happy or sad faces

8. What should we do after training a machine learning algorithm using a training dataset?

• Nothing. We should just send it out in the world to do its job — it's now ready!
• Print the dataset on paper.
• Test it on a different dataset (without labels) to pick out where it is making mistakes
• Stop using the dataset because it's impossible to know whether it s accurate or not.

A neural network is a type of machine learning algorithm that passes information from node to node, similar to the human brain.

• True
• False

One of the challenges of using neural networks is that we can t see what features the algorithms are picking out – a concept called a “black box”.

• True
• False