Consider the following Python code using Gensim's FastText:

medium📝 Predict Output Q4 of 15

NLP - Word Embeddings

from gensim.models import FastText
sentences = [['data', 'science'], ['machine', 'learning']]
model = FastText(sentences, vector_size=8, window=2, min_count=1, epochs=4)
print(model.wv['machine'].shape)

What will be the output?

A(1, 8)

B(4, 8)

C(8,)

DError: KeyError

Step-by-Step Solution

Solution:

Step 1: Identify vector size
The model is initialized with vector_size=8, so each word vector has 8 dimensions.
Step 2: Check word presence
'machine' is in the training sentences, so no KeyError occurs.
Step 3: Understand output shape
model.wv['machine'] returns a 1D numpy array of length 8, so shape is (8,)
Final Answer:
(8,) -> Option C
Quick Check:
Vector size matches output shape [OK]

Quick Trick: Output shape equals vector_size tuple [OK]

Common Mistakes:

MISTAKES

Expecting a 2D array shape
Assuming KeyError for known words
Confusing epochs with vector dimensions

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More NLP Quizzes

Consider the following Python code using Gensim's FastText:

Step 1: Identify vector size

Step 2: Check word presence

Step 3: Understand output shape

Final Answer:

Quick Check:

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