| What is Natural Language Processing (NLP)? |
| What are the main components of NLP? |
| What is the difference between NLP, NLU, and NLG? |
| What are some real-world applications of NLP? |
| What are stop words in NLP? |
| What is tokenization? |
| What is the difference between stemming and lemmatization? |
| What is POS (Part-of-Speech) tagging? |
| What are n-grams? Why are they used? |
| What is Named Entity Recognition (NER)? |
| Why is text preprocessing important in NLP? |
| What is TF-IDF? How is it different from bag-of-words? |
| What is the difference between count vectorization and TF-IDF? |
| How do you handle missing or noisy text data? |
| What are common text normalization techniques? |
| What are word embeddings? |
| Explain Word2Vec and its two architectures. |
| What is the difference between Word2Vec and GloVe? |
| What are contextual embeddings? Give examples. |
| What is subword embedding? |
| What is a language model in NLP? |
| What is the difference between statistical and neural language models? |
| What is perplexity in language modeling? |
| What is a unigram/bigram/trigram language model? |
| What are pre-trained language models? |
| What is dependency parsing? |
| What is constituency parsing? |
| What is coreference resolution? |
| What is co-occurrence matrix? |
| Explain Latent Semantic Analysis (LSA). |
| What is topic modeling? How does LDA work? |
| What is attention mechanism in NLP? |
| Explain the concept of transformers in NLP. |
| What is BERT? How is it different from traditional models? |
| What is fine-tuning in BERT? |
| How do you build a text classification model? |
| What is the difference between classification and clustering in NLP? |
| What is sentiment analysis? How do you perform it? |
| How do you handle imbalanced data in text classification? |
| What are some popular evaluation metrics for NLP models? |
| What is an RNN? How is it used in NLP? |
| What are LSTM and GRU? |
| What is the vanishing gradient problem? |
| How do transformers overcome the limitations of RNNs? |
| What is a sequence-to-sequence model? |
| What is speech recognition? |
| What is a chatbot? What are the types of chatbots? |
| What is intent recognition? |
| What is slot filling? |
| What is dialogue management? |
| How would you build a sentiment analysis system? |
| How do you evaluate the quality of a text summarization model? |
| How would you deploy an NLP model in production? |
| What are some popular NLP libraries in Python? |
| How do you handle out-of-vocabulary (OOV) words? |
| What are large language models (LLMs)? |
| What is GPT? How is it trained? |
| What is the difference between GPT and BERT? |
| What are the ethical concerns in NLP? |
| How can NLP models be biased? |
| What is the role of CNNs in NLP? |
| How does an attention mechanism work? |
| What is the difference between self-attention and cross-attention? |
| Explain the architecture of the Transformer model. |
| What are encoder and decoder in transformers? |
| What is positional encoding in transformers? |
| What is masked language modeling? |
| What is the difference between GPT-style and BERT-style training? |
| What is a causal language model? |
| How does RoBERTa differ from BERT? |
| What is transfer learning in NLP? |
| How do you fine-tune a pre-trained transformer model? |
| What are frozen layers and trainable layers in fine-tuning? |
| What are the benefits of using pre-trained embeddings? |
| What is zero-shot learning in NLP? |
| How does extractive summarization work? |
| How is abstractive summarization different from extractive? |
| What is the architecture behind QA models like BERT QA? |
| How do you evaluate the accuracy of a summarization model? |
| What metrics are used to evaluate QA systems? |
| What is BLEU score? |
| What is ROUGE score? |
| What is METEOR score? |
| What is perplexity and how is it interpreted? |
| What are precision, recall, and F1-score in NLP classification? |
| What is cross-lingual NLP? |
| How does mBERT work for multiple languages? |
| What is code-switching and how is it handled in NLP? |
| What are the challenges in multilingual NLP? |
| What is XLM-R? |
| What are common biases in NLP datasets? |
| How can we reduce gender bias in NLP models? |
| What is explainable AI (XAI) in the context of NLP? |
| What are adversarial examples in NLP? |
| What is differential privacy in NLP? |
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