Cosine similarity in NLP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

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

NLP

dot_product = sum(a * b for a, b in zip(vec1, [1]))

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

Avec3

Bvec2

Cvec1

Dvector

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same vector twice, which calculates the dot product of a vector with itself.

The dot product multiplies corresponding elements of two vectors and sums them. Here, vec2 is the second vector to multiply with vec1.

2fill in blank

medium

Complete the code to calculate the magnitude (length) of a vector.

NLP

magnitude = sum(x[1]2 for x in vec) ** 0.5

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

A**

B+

C*

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition or multiplication instead of exponentiation to square elements.

The magnitude is the square root of the sum of squares of vector elements. So each element is squared using ** 2.

3fill in blank

hard

Fix the error in the cosine similarity formula by completing the denominator.

NLP

cos_sim = dot_product / (magnitude1 [1] magnitude2)

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

A*

B/

C-

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition or division instead of multiplication in the denominator.

The denominator of cosine similarity is the product of the magnitudes of the two vectors, so the operator is *.

4fill in blank

hard

Fill both blanks to complete the dictionary comprehension that maps words to their vector lengths if length is greater than 3.

NLP

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

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

Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of its length.

Using < instead of > in the condition.

The dictionary comprehension creates a mapping from each word to its length, but only for words longer than 3 characters. So len(word) is the value, and the condition uses >.

5fill in blank

hard

Fill all three blanks to create a dictionary of words mapped to their lengths, but only include words with length greater than 2.

NLP

result = [1]: [2] for [3] in word_list if len([3]) > 2}

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

Aword

Blen(word)

Cword_list

Attempts:

3 left

💡 Hint

Common Mistakes

Using the list name as loop variable.

Mixing variable names inconsistently.

The dictionary comprehension maps each word to its length len(word). The loop variable is word iterating over word_list. The condition filters words longer than 2.