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NATURAL LANGUAGE PROCESSING WORKSHOP - : design and build nlp projects [electronic resource]
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| 자료유형 | E-Book |
|---|---|
| 서명/저자사항 | NATURAL LANGUAGE PROCESSING WORKSHOP -[electronic resource] :design and build nlp projects. |
| 발행사항 | [S.l.] : PACKT PUBLISHING LIMITED, 2020. |
| 형태사항 | 1 online resource |
| 소장본 주기 | Master record variable field(s) change: 050, 082, 650 - OCLC control number change |
| ISBN | 9781800200807 1800200803 |
| 내용주기 | Cover -- FM -- Copyright -- Table of Contents -- Preface -- Chapter 1: Introduction to Natural Language Processing -- Introduction -- History of NLP -- Text Analytics and NLP -- Exercise 1.01: Basic Text Analytics -- Various Steps in NLP -- Tokenization -- Exercise 1.02: Tokenization of a Simple Sentence -- PoS Tagging -- Exercise 1.03: PoS Tagging -- Stop Word Removal -- Exercise 1.04: Stop Word Removal -- Text Normalization -- Exercise 1.05: Text Normalization -- Spelling Correction -- Exercise 1.06: Spelling Correction of a Word and a Sentence -- Stemming -- Exercise 1.07: Using Stemming Lemmatization -- Exercise 1.08: Extracting the Base Word Using Lemmatization -- Named Entity Recognition (NER) -- Exercise 1.09: Treating Named Entities -- Word Sense Disambiguation -- Exercise 1.10: Word Sense Disambiguation -- Sentence Boundary Detection -- Exercise 1.11: Sentence Boundary Detection -- Activity 1.01: Preprocessing of Raw Text -- Kick Starting an NLP Project -- Data Collection -- Data Preprocessing -- Feature Extraction -- Model Development -- Model Assessment -- Model Deployment -- Summary -- Chapter 2: Feature Extraction Methods -- Introduction -- Types of Data Categorizing Data Based on Structure -- Categorizing Data Based on Content -- Cleaning Text Data -- Tokenization -- Exercise 2.01: Text Cleaning and Tokenization -- Exercise 2.02: Extracting n-grams -- Exercise 2.03: Tokenizing Text with Keras and TextBlob -- Types of Tokenizers -- Exercise 2.04: Tokenizing Text Using Various Tokenizers -- Stemming -- RegexpStemmer -- Exercise 2.05: Converting Words in the Present Continuous Tense into Base Words with RegexpStemmer -- The Porter Stemmer -- Exercise 2.06: Using the Porter Stemmer -- Lemmatization -- Exercise 2.07: Performing Lemmatization Exercise 2.08: Singularizing and Pluralizing Words -- Language Translation -- Exercise 2.09: Language Translation -- Stop-Word Removal -- Exercise 2.10: Removing Stop Words from Text -- Activity 2.01: Extracting Top Keywords from the News Article -- Feature Extraction from Texts -- Extracting General Features from Raw Text -- Exercise 2.11: Extracting General Features from Raw Text -- Exercise 2.12: Extracting General Features from Text -- Bag of Words (BoW) -- Exercise 2.13: Creating a Bag of Words -- Zipf's Law -- Exercise 2.14: Zipf's Law -- Term Frequency-Inverse Document Frequency (TFIDF) Exercise 2.15: TFIDF Representation -- Finding Text Similarity -- Application of Feature Extraction -- Exercise 2.16: Calculating Text Similarity Using Jaccard and Cosine Similarity -- Word Sense Disambiguation Using the Lesk Algorithm -- Exercise 2.17: Implementing the Lesk Algorithm Using String Similarity and Text Vectorization -- Word Clouds -- Exercise 2.18: Generating Word Clouds -- Other Visualizations -- Exercise 2.19: Other Visualizations Dependency Parse Trees and Named Entities -- Activity 2.02: Text Visualization -- Summary -- Chapter 3: Developing a Text Classifier -- Introduction |
| 일반주제명 | Natural language processing (Computer science) |
| 언어 | 영어 |
| 기타형태 저록 | Original18002084219781800208421 |
| 대출바로가기 | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2581635 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00018862 | 006.35 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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