Can you explain what BERT is in the context of NLP?
BERT stands for Bidirectional Encoder Representations from Transformers. It's a model designed to understand the context of words in a sentence.
How does BERT differ from traditional NLP models?
Unlike traditional models that read text sequentially, BERT reads text in both directions, allowing it to grasp context better.
What are some applications of BERT in real-world scenarios?
BERT is used in various applications like search engines, chatbots, and sentiment analysis to improve understanding and relevance.
Is BERT the best model for all NLP tasks?
While BERT is powerful, it's not always the best choice. Depending on the task, other models like GPT or T5 might perform better.
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