Hands-On Implementation of NLP Models
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"Hands-On Implementation of NLP Models" is a comprehensive guide designed to bridge the gap between theoretical concepts and practical applications in Natural Language Processing (NLP). The book covers fundamental NLP concepts, advanced models, and real-world applications.Chapters include an introduction to NLP, basics like text preprocessing and tokenization, classical models such as Naive Bayes and Support Vector Machines, and deep learning techniques including LSTM and transformer models like BERT and GPT. Practical chapters demonstrate building NLP models with Python, real-world case studi...
"Hands-On Implementation of NLP Models" is a comprehensive guide designed to bridge the gap between theoretical concepts and practical applications in Natural Language Processing (NLP). The book covers fundamental NLP concepts, advanced models, and real-world applications.Chapters include an introduction to NLP, basics like text preprocessing and tokenization, classical models such as Naive Bayes and Support Vector Machines, and deep learning techniques including LSTM and transformer models like BERT and GPT. Practical chapters demonstrate building NLP models with Python, real-world case studies, and end-to-end project implementations.
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