Natural Language Processing Basics
Learners explore techniques that enable machines to understand and process human language. Students study tokenization, word embeddings, and language modeling approaches. Techniques such as sequence-to-sequence models support tasks including translation and summarization. Applications extend to chatbots, sentiment analysis, and information retrieval. It emphasizes semantic understanding and contextual representation. NLP forms a core area of AI research and industry use.
Language Processing Elements:
- Text preprocessing techniques
- Semantic representation
- Language understanding models
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