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Cover: 9781009012652 | Deep Learning for Natural Language Processing | Valenzuela-Escárcega
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Deep Learning for Natural Language Processing
Taschenbuch von Mihai Surdeanu (u. a.)
Sprache: Englisch

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Beschreibung
A clear, accessible introduction to deep learning for natural language processing (NLP), this book is ideal for readers without a background in machine learning and NLP. It covers the necessary theoretical context using minimal jargon also covers practical aspects, using actual Python code for the neural architectures discussed.
A clear, accessible introduction to deep learning for natural language processing (NLP), this book is ideal for readers without a background in machine learning and NLP. It covers the necessary theoretical context using minimal jargon also covers practical aspects, using actual Python code for the neural architectures discussed.
Über den Autor
Mihai Surdeanu is Associate Professor in the Computer Science Department at the University of Arizona. He works in both academia and industry on NLP systems that process and extract meaning from natural language.
Inhaltsverzeichnis
Preface; 1. Introduction; 2. The perception; 3. Logistic regression; 4. Implementing text classfication using perceptron and LR; 5. Feed forward neural networks; 6. Best practices in deep learning; 7. Implementing text classification with feed forward networks; 8. Distributional hypothesis and representation learning; 9. Implementing text classification using word embedding; 10. Recurrent neural networks; 11. Implementing POS tagging using RNNs; 12. Contexualized embeddings and transformer networks; 13. Using transformers with the hugging face library; 14. Encoder-decoder methods; 15. Implementing encoder-decoder methods; 16. Neural architecture for NLP applications; Appendix A: Overview of the python language and the key libraries; Appendix B: Character endcodings: ASCII and unicode.
Details
Erscheinungsjahr: 2024
Genre: Importe
Rubrik: Sprachwissenschaft
Medium: Taschenbuch
ISBN-13: 9781009012652
ISBN-10: 1009012657
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Surdeanu, Mihai
Valenzuela-Escárcega, Marco Antonio
Hersteller: Cambridge University Press
Maße: 229 x 152 x 19 mm
Von/Mit: Mihai Surdeanu (u. a.)
Erscheinungsdatum: 12.01.2024
Gewicht: 0,499 kg
Artikel-ID: 127744623
Über den Autor
Mihai Surdeanu is Associate Professor in the Computer Science Department at the University of Arizona. He works in both academia and industry on NLP systems that process and extract meaning from natural language.
Inhaltsverzeichnis
Preface; 1. Introduction; 2. The perception; 3. Logistic regression; 4. Implementing text classfication using perceptron and LR; 5. Feed forward neural networks; 6. Best practices in deep learning; 7. Implementing text classification with feed forward networks; 8. Distributional hypothesis and representation learning; 9. Implementing text classification using word embedding; 10. Recurrent neural networks; 11. Implementing POS tagging using RNNs; 12. Contexualized embeddings and transformer networks; 13. Using transformers with the hugging face library; 14. Encoder-decoder methods; 15. Implementing encoder-decoder methods; 16. Neural architecture for NLP applications; Appendix A: Overview of the python language and the key libraries; Appendix B: Character endcodings: ASCII and unicode.
Details
Erscheinungsjahr: 2024
Genre: Importe
Rubrik: Sprachwissenschaft
Medium: Taschenbuch
ISBN-13: 9781009012652
ISBN-10: 1009012657
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Surdeanu, Mihai
Valenzuela-Escárcega, Marco Antonio
Hersteller: Cambridge University Press
Maße: 229 x 152 x 19 mm
Von/Mit: Mihai Surdeanu (u. a.)
Erscheinungsdatum: 12.01.2024
Gewicht: 0,499 kg
Artikel-ID: 127744623
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