This ebook introduces Natural Language Processing as the field focused on enabling machines to understand and generate human language for real-world applications. It outlines key techniques including tokenization, stemming, lemmatization, part-of-speech tagging, parsing, and sentiment analysis, showing how these methods transform unstructured text into structured data for analysis. The paper emphasizes machine learning’s role in advancing NLP, especially through supervised and unsupervised models, as well as deep learning approaches like recurrent and transformer-based networks. Applications span chatbots, translation, search engines, and information retrieval, demonstrating NLP’s growing impact across industries.

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