Quiz A1

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Quiz A1

Quiz for Stream A 1. Introduction to AI and Neural Networks

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1a. 'Training a surgical robot to perform a specific procedure safely and efficiently. ' would be an example of ________ Learning *

3 points

1b. 'Classifying known dermatological skin lesions from photographs.' would be an example of ________ Learning *

1 point

1c. 'Finding new genetic associations with a particular disease using genomic data.' would be an example of ________ Learning *

1 point

2a. Accuracy is measured with a _______function. *

1 point

2b. Weights are updated by a process called _________ *

1 point

2c. Calculations performed by 'neurons' are called ______ functions. *

1 point

3. Which of the following is true about Gradient descent? *

1 point

If the learning rate is too small, it will never reach the minimum loss

If the learning rate is too big, it will never reach the minimum loss

A smaller learning rate will be faster at approaching the minimum loss

A larger learning rate will more precisely approach the minimum loss

4. Match the prediction with its data type. *

6 points

Binary

Nominal

Ordinal

Discrete

Continuous

Predicting if a patient has dementia or not based on an MRI scan.

Predicting the diagnosis of patient's abdominal pain based on symptoms

Predicting the optimal insulin dosing to treat diabetes.

Predicting the number of future hospitalizations in a patient with heart failure.

Predicting cancer staging based on blood test results.

Predicting the need for chemotherapy based on biopsy results.

Binary

Nominal

Ordinal

Discrete

Continuous

Predicting if a patient has dementia or not based on an MRI scan.

Predicting the diagnosis of patient's abdominal pain based on symptoms

Predicting the optimal insulin dosing to treat diabetes.

Predicting the number of future hospitalizations in a patient with heart failure.

Predicting cancer staging based on blood test results.

Predicting the need for chemotherapy based on biopsy results.

5. Choose the correct order of steps in a training epoch. *

1 point

Input data, propagate through model, evaluate loss, backpropagate, output predictions

Input data, evaluate loss, propagate through model, output predictions, backpropagate

Input data, propagate through model, backpropagate, evaluate loss, output predictions

Input data, propagate through model, output predictions, evaluate loss, backpropagate

6. Learning rate, batch size, and number of epochs can all be adjusted to improve learning. These (and others) are collectively called __________

1 point

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