Machine Learning (Project Stem)

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

• True

• False

Machine learning is a type of AI algorithm used frequently today.

• True

• False

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

• Poodle

• Bulldog

• Garbage Truck

• German Shepherd

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

• Goldfish

• Shark

• Boat

• Swordfish

How can humans supervise machine learning?

• By putting laptops in laptop bags

• By providing organized and labeled training data

• By explaining to an AI what steps to take, in human language

• 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 baseball caps from top hats, or elephants from rhinoceroses. 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 mad or a joyful face, what should the dataset we use contain – to make sure it is diverse?

• Both mad and joyful face sketches drawn by many different types of people

• Only joyful face sketches drawn by many different types of people

• Only mad face sketches drawn by many different types of people

• Songs about people with mad or joyful faces

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

• Nothing. We should just let it do its job without anything more — it's now ready!

• Draw a picture of 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 similar to the human brain, that passes information from node to node.

• True

• False

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

• True

• False