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What is the main purpose of using embeddings in NLP?
What is the main purpose of using embeddings in NLP?
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What is the main purpose of using embeddings in NLP?
To reduce the dimensionality of text data
To convert text into a format suitable for machine learning
To capture semantic meaning of words
To improve the speed of tokenization
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Embeddings are used to capture the semantic meaning of words in a continuous vector space.
Questions & Step-by-step Solutions
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Q: What is the main purpose of using embeddings in NLP?
Solution:
Embeddings are used to capture the semantic meaning of words in a continuous vector space.
Steps: 5
Show Steps
Step 1: Understand that words have meanings.
Step 2: Realize that computers need a way to understand these meanings.
Step 3: Learn that embeddings are a method to represent words as numbers.
Step 4: Know that these numbers are organized in a way that similar words are closer together.
Step 5: Recognize that this helps computers understand relationships between words.
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