Natural Language Processing and Computational Linguistics
Bhargav Srinivasa-Desikan
- 出版商: Packt Publishing
- 出版日期: 2018-06-29
- 售價: $1,780
- 貴賓價: 9.5 折 $1,691
- 語言: 英文
- 頁數: 306
- 裝訂: Paperback
- ISBN: 178883853X
- ISBN-13: 9781788838535
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相關分類:
DeepLearning
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相關翻譯:
自然語言處理與計算語言學 (簡中版)
相關主題
商品描述
Learn NLP working through data and understand statistical NLP and deep learning
Key Features
- A soup-to-nuts introduction to natural language processing
- A introduction to 4 language processing frameworks, each with their strengths and particular application area
- An introduction to NLP with deep learning and Keras.
Book Description
Natural language processing is like the secret sauce of artificial intelligence and machine learning. It is basically impossible to process unstructured data without it, and we should not forget that all data starts its existence as unstructured or semi-structured data.
This book is a broad introduction to natural language processing, travelling through data cleaning and computational linguistics, before presenting the more sophisticated areas of statistical NLP and deep learning. Correspondingly, the author emphasizes that the best frameworks should be used for applications they are best suited for, for instance, GenSim for topic modeling or Keras for deep learning.
In all, Beginning Natural Language Processing does not go deep into libraries and frameworks, but tries to get the reader fired up about the power of natural language processing.
What you will learn
- You will learn to clearly distinguish basic NLP terminology, e.g. you will know the difference between computational linguistics and natural language processing
- You will learn how to prepare text and corpora for analysis using computational linguistic methods
- Among other things, you will study the role of deep learning, particularly Keras, in the context of unstructured data, a role where RNNs and similar methods excel
- You will get to know the power of SpaCy in general NLP, a new open source framework focusing on natural language processing
- And you will learn how to apply GenSim for topic modeling and Scikit
- Learn for basic text processing
Who This Book Is For
Fluency in Python is assumed. Basic statistics is helpful. Given that this book introduces natural language processing from first principles, it helps, although it is not a requirement, to be familiar with basic linguistics.
商品描述(中文翻譯)
學習自然語言處理(NLP)的工作流程,並了解統計NLP和深度學習。
主要特點:
- 從頭到尾介紹自然語言處理。
- 介紹4種語言處理框架,每種都有其優勢和特定的應用領域。
- 介紹使用深度學習和Keras進行NLP。
書籍描述:
自然語言處理就像是人工智慧和機器學習的秘密武器。在處理非結構化數據時,幾乎不可能沒有它,而且我們不應該忘記所有數據最初都是非結構化或半結構化的。
本書是對自然語言處理的廣泛介紹,從數據清理和計算語言學開始,然後介紹統計NLP和深度學習的更高級領域。作者強調應該根據最適合的應用領域使用最佳框架,例如,用於主題建模的GenSim或用於深度學習的Keras。
總之,《自然語言處理入門》並不深入探討庫和框架,而是試圖讓讀者對自然語言處理的強大功能感到興奮。
你將學到什麼:
- 你將學會清楚地區分基本的NLP術語,例如你將了解計算語言學和自然語言處理之間的區別。
- 你將學習如何使用計算語言學方法為文本和語料庫進行分析的準備。
- 你將研究深度學習在非結構化數據背景下的作用,特別是Keras在其中的角色,這是RNN和類似方法擅長的領域。
- 你將了解SpaCy在一般NLP中的強大功能,這是一個新的開源框架,專注於自然語言處理。
- 你將學習如何應用GenSim進行主題建模和Scikit進行基本文本處理。
適合閱讀對象:
假設讀者熟悉Python,基本統計知識有所幫助。由於本書從基本原理介紹自然語言處理,熟悉基本語言學知識有所幫助,但不是必需的。