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深度學習
Spark NLP自然語言處理(影印版) 版權信息
- ISBN：9787564195113
- 條形碼：9787564195113 ; 978-7-5641-9511-3
- 裝幀：一般膠版紙
- 冊數：暫無
- 重量：暫無
- 所屬分類：>
Spark NLP自然語言處理(影印版) 內容簡介
如果您想構建使用自然語言文本的企業級應用程序，但不確定從哪里開始或使用什么工具，那么本實用指南將幫助您入門。Wisecube的首席數據科學家Alex Thomas向軟件工程師和數據科學家展示了如何使用深度學習和Apache Spark NLP庫構建可擴展的自然語言處理(NLP)應用程序。通過具體的例子、實踐和理論解釋，以及在Spark processing框架上使用NLP的動手練習，這本書教你從基本語言學和寫作系統到情緒分析和搜索引擎的一切。您還將探討開發基于文本的應用程序的一些特殊問題，比如性能。
Spark NLP自然語言處理(影印版) 目錄
Preface
Part I. Basics
1. Getting Started
Introduction
Other Tools
Setting Up Your Environment
Prerequisites
Starting Apache Spark
Checking Out the Code
Getting Familiar with Apache Spark
Starting Apache Spark with Spark NLP
Loading and Viewing Data in Apache Spark
Hello World with Spark NLP
2. Natural Language Basics
What Is Natural Language?
Origins of Language
Spoken Language Versus Written Language
Linguistics
Phonetics and Phonology
Morphology
Syntax
Semantics
Sociolinguistics: Dialects, Registers, and Other Varieties
Formality
Context
Pragmatics
Roman ]akobson
How To Use Pragmatics
Writing Systems
Origins
Alphabets
Abiads
Abugidas
Syllabaries
Logographs
Encodings
ASCII
Unicode
UTF-8
Exercises: Tokenizing
Tokenize English
Tokenize Greek
Tokenize Ge'ez (Amharic)
Resources
3. NLP on Apache Spark
Parallelism, Concurrency, Distributing Computation
Parallelization Before Apache Hadoop
MapReduce and Apache Hadoop
Apache Spark
Architecture of Apache Spark
Physical Architecture
Logical Architecture
Spark SQL and Spark MLlib
Transformers
Estimators and Models
Evaluators
NLP Libraries
Functionality Libraries
Annotation Libraries
NLP in Other Libraries
Spark NLP
Annotation Library
Stages
Pretrained Pipelines
Finisher
Exercises: Build a Topic Model
Resources
4. Deep Learning Basics
Gradient Descent
Backpropagation
Convolutional Neural Networks
Filters
Pooling
Recurrent Neural Networks
Backpropagation Through Time
Elman Nets
LSTMs
Exercise 1
Exercise 2
Resources
Part II. Building Blocks
5. Processing Words
6. Information Retrieval
7. Classification and Regression
8. Sequence Modeling with Keras
9. Information Extraction
10. Topic Modeling
11. Word Embeddings
Part III. Applications
12. Sentiment Analysis and Emotion Detection
13. Building Knowledqe Bases
14. Search Engine
15. Chatbot
16. Object Character Recognition
Part IV. Building NLP Systems
17. Supporting Multiple Languages
18. Human Labeling
19. Productionizing NLP Applications
Glossary
Index
Part I. Basics
1. Getting Started
Introduction
Other Tools
Setting Up Your Environment
Prerequisites
Starting Apache Spark
Checking Out the Code
Getting Familiar with Apache Spark
Starting Apache Spark with Spark NLP
Loading and Viewing Data in Apache Spark
Hello World with Spark NLP
2. Natural Language Basics
What Is Natural Language?
Origins of Language
Spoken Language Versus Written Language
Linguistics
Phonetics and Phonology
Morphology
Syntax
Semantics
Sociolinguistics: Dialects, Registers, and Other Varieties
Formality
Context
Pragmatics
Roman ]akobson
How To Use Pragmatics
Writing Systems
Origins
Alphabets
Abiads
Abugidas
Syllabaries
Logographs
Encodings
ASCII
Unicode
UTF-8
Exercises: Tokenizing
Tokenize English
Tokenize Greek
Tokenize Ge'ez (Amharic)
Resources
3. NLP on Apache Spark
Parallelism, Concurrency, Distributing Computation
Parallelization Before Apache Hadoop
MapReduce and Apache Hadoop
Apache Spark
Architecture of Apache Spark
Physical Architecture
Logical Architecture
Spark SQL and Spark MLlib
Transformers
Estimators and Models
Evaluators
NLP Libraries
Functionality Libraries
Annotation Libraries
NLP in Other Libraries
Spark NLP
Annotation Library
Stages
Pretrained Pipelines
Finisher
Exercises: Build a Topic Model
Resources
4. Deep Learning Basics
Gradient Descent
Backpropagation
Convolutional Neural Networks
Filters
Pooling
Recurrent Neural Networks
Backpropagation Through Time
Elman Nets
LSTMs
Exercise 1
Exercise 2
Resources
Part II. Building Blocks
5. Processing Words
6. Information Retrieval
7. Classification and Regression
8. Sequence Modeling with Keras
9. Information Extraction
10. Topic Modeling
11. Word Embeddings
Part III. Applications
12. Sentiment Analysis and Emotion Detection
13. Building Knowledqe Bases
14. Search Engine
15. Chatbot
16. Object Character Recognition
Part IV. Building NLP Systems
17. Supporting Multiple Languages
18. Human Labeling
19. Productionizing NLP Applications
Glossary
Index
展開全部
Spark NLP自然語言處理(影印版) 作者簡介
亞歷克斯·托馬斯是Wisecube的首席數據科學家。他將自然語言處理和機器學習運用于臨床數據、身份數據、雇主和求職者數據以及如今的生化數據。Alex從09版本開始使用Apache Spark，在工作中也用過包括UIMA和OpenNLP在內的多種NLP庫和框架。
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