Understanding Natural Language Processing
Understanding Natural Language Processing strives to elucidate the fundamental principles of natural language processing (NLP) from various angles…
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Understanding Natural Language Processing
Understanding Natural Language Processing strives to elucidate the fundamental principles of natural language processing (NLP) from various angles, encompassing conceptual, mathematical, and algorithmic perspectives, along with practical insights into tools and software usage.
The primary emphasis, however, is directed towards prompting readers to contemplate applications in the realm of natural language processing, enabling them to seamlessly integrate NLP components into real-time applications. The concepts are explored through the lens of machine learning and deep learning methodologies, accompanied by relevant use cases threaded throughout the chapters.
Features:
- Discusses comparison of language models, basic vector models and neural language models
- Introduces basic concepts of word, morphology and semantics
- Explains word embedding and deep learning models including pre-trained models
- Emphasizes on machine learning and deep learning approaches to NLP tasks – part-of speech tagging, syntactic processing, semantic processing and discourse and dialog systems including the latest ChatGPT architecture
- Illustrates NLP from an application perspective – machine learning and deep learning approaches to text categorization, machine translation, information extraction, question answering and summarization
- Covers ethics of NLP including bias and fairness
- Rich pedagogy – objective-type questions, activities, case-studies and project-based learning exercises.
Book | |
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Author | Geetha |
Pages | 396 |
Year | 2024 |
ISBN | 9788119896004 |
Publisher | Pearson |
Language | English |
Uncategorized | |
Edition | 1/e |
Weight | 477 g |
Dimensions | 23.5 x 17.2 x 1.6 cm |
Binding | Paperback |