Why linear algebra matters in NumPy - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a 2x2 matrix using numpy.

NumPy

import numpy as np
matrix = np.array([1])
print(matrix)

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

A[1, 2, 3, 4]

B[[1, 2], 3, 4]

C[[1, 2, 3], [4, 5, 6]]

D[[1, 2], [3, 4]]

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a flat list instead of a list of lists.

Using uneven inner lists causing shape errors.

The correct way to create a 2x2 matrix is by passing a list of lists representing rows.

2fill in blank

medium

Complete the code to calculate the dot product of two vectors using numpy.

NumPy

import numpy as np
v1 = np.array([1, 2, 3])
v2 = np.array([4, 5, 6])
dot_product = np.[1](v1, v2)
print(dot_product)

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Adot

Badd

Ccross

Dmultiply

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiply which returns element-wise product.

Using cross which calculates cross product, not dot product.

The np.dot function calculates the dot product of two vectors.

3fill in blank

hard

Fix the error in the code to compute the inverse of a matrix using numpy.

NumPy

import numpy as np
matrix = np.array([[1, 2], [3, 4]])
inverse = np.linalg.[1](matrix)
print(inverse)

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Ainversed

Binverse

Cinv

Dinvert

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect function names like 'inverse' or 'invert'.

Trying to use non-existent functions causing AttributeError.

The correct numpy function to compute matrix inverse is np.linalg.inv.

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.

NumPy

words = ['data', 'science', 'is', 'fun']
lengths = { [1] : len([2]) for [1] in words if len([1]) > 3 }
print(lengths)

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Aword

Bwords

Cw

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using the list name instead of the loop variable inside len().

Using different variable names inconsistently.

We use the variable 'word' to iterate over 'words' and map each word to its length if length > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if length is greater than 2.

NumPy

words = ['AI', 'ML', 'Data', 'Code']
result = { [1] : [2] for [3] in words if len([3]) > 2 }
print(result)

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Aword.upper()

Blen(word)

Cword

Dwords

Attempts:

3 left

💡 Hint

Common Mistakes

Using the list name instead of the loop variable.

Not applying upper() to the key.

Using inconsistent variable names.

The comprehension uses 'word' as the loop variable, maps word.upper() to len(word) if length > 2.