Section 3 Quiz AI REVIEW (3.1-3.4)

5. What might we use as the training data?

4. In a supervised machine learning system, who might be directing or helping the AI learn?

11. What does the backpropagation algorithm do during these feedback loops?

6. How would the AI know what to classify each ball as? How might it know what to call each one?

2. How does a machine-learning AI learn on its own?

Is it beneficial for computer programmers not to know the features used in a neural network? 

7. In the marshmallow sorting system, what were the two classes of data that were given to the machine for training?

3. Without thinking about computers or AI, what do you think when you hear the word "supervised"?

Could the lack of visibility into the algorithm's picked features lead to issues when training a neural network?

8. What was the training data the model was given to learn from?

10. Did we have to tell Teachable Machine how to classify the data or did it figure it out on its own?

Did programmers need to know the features used in the Teachable Machine to categorize objects accurately?

1. What is machine learning (ML)?

What features did the AI utilize to predict if new data is "marshmallow" or "not marshmallow"?