Explore key resources related to **Natural Language Processing (NLP)**, a core subject for Computer Science and Engineering students. This includes important concepts, previous year exam papers, and reference materials.
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Important Concepts - NLP
Here are the key concepts for **Natural Language Processing**, essential for your exam preparation.
Text Preprocessing
- Tokenization
- Stop Word Removal
- Stemming and Lemmatization
- Vectorization (TF-IDF, Word2Vec)
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Part of Speech Tagging
- POS Tagging Algorithms
- POS Tags in NLP
- Applications of POS Tagging
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Named Entity Recognition (NER)
- Entity Detection
- NER Applications
- NER Algorithms
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Sentiment Analysis
- Text Classification
- Emotion Detection
- Opinion Mining
- Applications of Sentiment Analysis
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Language Models
- Bigram and Trigram Models
- RNN and LSTM
- Transformers and BERT
- GPT-3 and GPT-4
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