Natural language understanding with Python: combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
Cover -- Title Page -- Copyright -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1: Getting Started with Natural Language Understanding Technology -- Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications -- Understanding the basics o...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham ; Mumbai
Packt Publishing
[2023]
|
| Ausgabe: | 1st edition |
| Schlagworte: | |
| Zusammenfassung: | Cover -- Title Page -- Copyright -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1: Getting Started with Natural Language Understanding Technology -- Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications -- Understanding the basics of natural language -- Global considerations - languages, encodings, and translations -- The relationship between conversational AI and NLP -- Exploring interactive applications - chatbots and voice assistants -- Generic voice assistants -- Enterprise assistants -- Translation -- Education -- Exploring non-interactive applications -- Classification -- Sentiment analysis -- Spam and phishing detection -- Fake news detection -- Document retrieval -- Analytics -- Information extraction -- Translation -- Summarization, authorship, correcting grammar, and other applications -- A summary of the types of applications -- A look ahead - Python for NLP -- Summary -- Chapter 2: Identifying Practical Natural Language Understanding Problems -- Identifying problems that are the appropriate level of difficulty for the technology -- Looking at difficult applications of NLU -- Looking at applications that don't need NLP -- Training data -- Application data -- Taking development costs into account -- Taking maintenance costs into account -- A flowchart for deciding on NLU applications -- Summary -- Part 2: Developing and Testing Natural Language Understanding Systems -- Chapter 3: Approaches to Natural Language Understanding - Rule-Based Systems, Machine Learning, and Deep Learning -- Rule-based approaches -- Words and lexicons -- Part-of-speech tagging -- Grammar -- Parsing -- Semantic analysis -- Pragmatic analysis -- Pipelines -- Traditional machine learning approaches -- Representing documents -- Classification -- Deep learning approaches -- Pre-trained models. |
| Beschreibung: | 1 Online-Ressource (xxi, 303 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781804612996 |
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| 245 | 1 | 0 | |a Natural language understanding with Python |b combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |c Deborah A. Dahl |
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| author | Dahl, Deborah A. |
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| discipline | Informatik |
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| format | Electronic eBook |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:08:24Z |
| indexdate | 2024-07-10T10:06:42Z |
| institution | BVB |
| isbn | 9781804612996 |
| language | English |
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| physical | 1 Online-Ressource (xxi, 303 Seiten) Illustrationen, Diagramme |
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| publisher | Packt Publishing |
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| spelling | Dahl, Deborah A. Verfasser (DE-588)1127155210 aut Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems Deborah A. Dahl 1st edition Birmingham ; Mumbai Packt Publishing [2023] © 2023 1 Online-Ressource (xxi, 303 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Cover -- Title Page -- Copyright -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1: Getting Started with Natural Language Understanding Technology -- Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications -- Understanding the basics of natural language -- Global considerations - languages, encodings, and translations -- The relationship between conversational AI and NLP -- Exploring interactive applications - chatbots and voice assistants -- Generic voice assistants -- Enterprise assistants -- Translation -- Education -- Exploring non-interactive applications -- Classification -- Sentiment analysis -- Spam and phishing detection -- Fake news detection -- Document retrieval -- Analytics -- Information extraction -- Translation -- Summarization, authorship, correcting grammar, and other applications -- A summary of the types of applications -- A look ahead - Python for NLP -- Summary -- Chapter 2: Identifying Practical Natural Language Understanding Problems -- Identifying problems that are the appropriate level of difficulty for the technology -- Looking at difficult applications of NLU -- Looking at applications that don't need NLP -- Training data -- Application data -- Taking development costs into account -- Taking maintenance costs into account -- A flowchart for deciding on NLU applications -- Summary -- Part 2: Developing and Testing Natural Language Understanding Systems -- Chapter 3: Approaches to Natural Language Understanding - Rule-Based Systems, Machine Learning, and Deep Learning -- Rule-based approaches -- Words and lexicons -- Part-of-speech tagging -- Grammar -- Parsing -- Semantic analysis -- Pragmatic analysis -- Pipelines -- Traditional machine learning approaches -- Representing documents -- Classification -- Deep learning approaches -- Pre-trained models. Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Natürliche Sprache (DE-588)4041354-8 gnd rswk-swf Natürliche Sprache (DE-588)4041354-8 s Maschinelles Lernen (DE-588)4193754-5 s Python Programmiersprache (DE-588)4434275-5 s DE-604 |
| spellingShingle | Dahl, Deborah A. Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems Maschinelles Lernen (DE-588)4193754-5 gnd Python Programmiersprache (DE-588)4434275-5 gnd Natürliche Sprache (DE-588)4041354-8 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)4434275-5 (DE-588)4041354-8 |
| title | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |
| title_auth | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |
| title_exact_search | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |
| title_exact_search_txtP | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |
| title_full | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems Deborah A. Dahl |
| title_fullStr | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems Deborah A. Dahl |
| title_full_unstemmed | Natural language understanding with Python combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems Deborah A. Dahl |
| title_short | Natural language understanding with Python |
| title_sort | natural language understanding with python combine natural language technology deep learning and large language models to create human like language comprehension in computer systems |
| title_sub | combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems |
| topic | Maschinelles Lernen (DE-588)4193754-5 gnd Python Programmiersprache (DE-588)4434275-5 gnd Natürliche Sprache (DE-588)4041354-8 gnd |
| topic_facet | Maschinelles Lernen Python Programmiersprache Natürliche Sprache |
| work_keys_str_mv | AT dahldeboraha naturallanguageunderstandingwithpythoncombinenaturallanguagetechnologydeeplearningandlargelanguagemodelstocreatehumanlikelanguagecomprehensionincomputersystems |