Identify the error in this Word2Vec training code snippet: from gensim.models import Word2Vec sentences = [['data', 'science'], ['deep', 'learning']] model = Word2Vec(sentences, vector_size=100, window=5, sg=2) model.train(sentences, total_examples=2, epochs=10)

medium📝 Debug Q6 of 15

NLP - Word Embeddings

Asg parameter value 2 is invalid; should be 0 or 1

Bvector_size must be less than window size

Ctrain method missing required callbacks argument

Dtotal_examples should be number of words, not sentences

Step-by-Step Solution

Solution:

Step 1: Check valid values for sg parameter
sg can only be 0 (CBOW) or 1 (Skip-gram). 2 is invalid.
Step 2: Verify other parameters
vector_size and window sizes are valid; train method usage is correct.
Final Answer:
sg parameter value 2 is invalid; should be 0 or 1 -> Option A
Quick Check:
sg must be 0 or 1 [OK]

Quick Trick: sg parameter only accepts 0 or 1 [OK]

Common Mistakes:

MISTAKES

Using invalid sg values
Confusing vector_size and window constraints
Misunderstanding train method parameters

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Identify the error in this Word2Vec training code snippet: from gensim.models import Word2Vec sentences = [['data', 'science'], ['deep', 'learning']] model = Word2Vec(sentences, vector_size=100, window=5, sg=2) model.train(sentences, total_examples=2, epochs=10)

Step 1: Check valid values for sg parameter

Step 2: Verify other parameters

Final Answer:

Quick Check:

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