Machine learning vs rule-based systems in AI for Everyone - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a rule-based system that checks if a number is positive.

AI for Everyone

def is_positive(num):
    return num [1] 0

Drag options to blanks, or click blank then click option'

A>

B<

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' will check for negative numbers.

The rule-based system checks if the number is greater than zero to decide if it is positive.

2fill in blank

medium

Complete the code to train a simple machine learning model using scikit-learn.

AI for Everyone

from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.[1](X_train, y_train)

Drag options to blanks, or click blank then click option'

Apredict

Bfit

Ctransform

Dscore

Attempts:

3 left

💡 Hint

Common Mistakes

Using predict instead of fit will cause an error because the model is not trained yet.

The fit method trains the model on the training data.

3fill in blank

hard

Fix the error in the code that predicts labels using a trained model.

AI for Everyone

predictions = model.[1](X_test)

Drag options to blanks, or click blank then click option'

Apredict

Bfit

Ctransform

Dscore

Attempts:

3 left

💡 Hint

Common Mistakes

Using fit here will retrain the model instead of predicting.

The predict method is used to get predictions from the model on new data.

4fill in blank

hard

Fill both blanks to create a simple rule-based decision function.

AI for Everyone

def decide_action(temp):
    if temp [1] 30:
        return '[2]'
    else:
        return 'Stay inside'

Drag options to blanks, or click blank then click option'

A>

B<

CGo outside

DStay inside

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' will reverse the logic.

The function returns 'Go outside' if the temperature is greater than 30, otherwise 'Stay inside'.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps words to their lengths if length is greater than 3.

AI for Everyone

lengths = { [1]: [2] for [3] in words if len([3]) > 3 }

Drag options to blanks, or click blank then click option'

Aword

Blen(word)

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable name not defined in the loop will cause an error.

This dictionary comprehension creates a dictionary where keys are words and values are their lengths, but only for words longer than 3 characters.