What is NLP vectorization and why is it important?
An example of an AI chatbot conversation about NLP vectorization and its significance in AI.
What is NLP vectorization and why is it important?
NLP vectorization is the process of converting text into numerical vectors, enabling machines to understand and process language.
How does vectorization help in natural language processing?
Vectorization allows algorithms to analyze text data mathematically, facilitating tasks like sentiment analysis and topic modeling.
What are some common techniques for vectorization?
Common techniques include Bag of Words, TF-IDF, and Word Embeddings like Word2Vec and GloVe.
Can you explain Word Embeddings in more detail?
Sure! Word Embeddings represent words in a continuous vector space, capturing semantic relationships between them.
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