Machine learning concept in Intro to Computing - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the machine learning library.

Intro to Computing

import [1]

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

Anumpy

Btensorflow

Cpandas

Dmatplotlib

Attempts:

3 left

💡 Hint

Common Mistakes

Importing numpy instead of tensorflow

Importing pandas which is for data manipulation

Importing matplotlib which is for plotting

TensorFlow is a popular library used for machine learning tasks.

2fill in blank

medium

Complete the code to create a simple linear regression model using scikit-learn.

Intro to Computing

from sklearn.linear_model import [1]
model = [1]()

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

ALinearRegression

BLogisticRegression

CDecisionTreeClassifier

DKMeans

Attempts:

3 left

💡 Hint

Common Mistakes

Using LogisticRegression which is for classification

Using DecisionTreeClassifier which is for classification

Using KMeans which is for clustering

LinearRegression is the class used to create a linear regression model in scikit-learn.

3fill in blank

hard

Fix the error in the code to split data into training and testing sets with test_size=0.2.

Intro to Computing

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=[1], random_state=42)

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

A0.5

B50

C0.2

D'0.2'

Attempts:

3 left

💡 Hint

Common Mistakes

Using an integer like 50 instead of a float

Passing the number as a string

Using a value greater than 1

The test_size parameter expects a float between 0 and 1 representing the proportion of the dataset to include in the test split.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if the length is greater than 3.

Intro to Computing

{word: [1] for word in words if [2]

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

Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value

Checking if the word is greater than 3 (which is invalid)

Not using len(word) in the condition

The dictionary comprehension maps each word to its length using len(word). The condition filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their frequencies only if frequency is greater than 1.

Intro to Computing

{ [1]: [2] for [3], [2] in word_counts.items() if [2] > 1 }

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

Aword.upper()

Bcount

Cword

Dfreq

Attempts:

3 left

💡 Hint

Common Mistakes

Using the original word as key without uppercasing

Using inconsistent variable names for count

Not filtering counts greater than 1

The comprehension maps the uppercase version of each word to its count, iterating over word_counts items where count is greater than 1.