[Solved] What will be the output of the following code snippet? from gensim.... What will be the output of the following code snippet? | NLP

NLP - Word Embeddings

What will be the output of the following code snippet? from gensim.models import Word2Vec sentences = [['hello', 'world'], ['hello', 'machine', 'learning']] model = Word2Vec(sentences, vector_size=10, window=1, sg=1, min_count=1) print(len(model.wv))

A4

B3

C2

D1

Step-by-Step Solution

Solution:

Step 1: Count unique words in sentences
Words are 'hello', 'world', 'machine', 'learning' -- total 4 unique words.
Step 2: Check min_count parameter effect
min_count=1 means all words with frequency >=1 are included.
Final Answer:
4 -> Option A
Quick Check:
Vocabulary size = unique words with min_count ≥1 [OK]

Quick Trick: Vocabulary size equals unique words meeting min_count [OK]

Common Mistakes:

MISTAKES

Counting total words instead of unique
Ignoring min_count filtering
Assuming default min_count excludes words

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More NLP Quizzes

What will be the output of the following code snippet?

Step 1: Count unique words in sentences

Step 2: Check min_count parameter effect

Final Answer:

Quick Check:

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