Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning Using Python 2/e
暫譯: 自然語言處理食譜：使用 Python 解鎖文本數據的機器學習與深度學習（第二版）

Kulkarni, Akshay, Shivananda, Adarsha

Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning Using Python 2/e
  • 出版商: Apress
  • 出版日期: 2021-08-26
  • 售價: $2,350
  • 貴賓價: 9.5 折 $2,233
  • 語言: 英文
  • 頁數: 312
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484273508
  • ISBN-13: 9781484273500
  • 相關分類: Python、程式語言、Machine Learning、DeepLearning

    • 海外代購書籍(需單獨結帳)

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商品描述

Focus on implementing end-to-end projects using Python and leverage state-of-the-art algorithms. This book teaches you to efficiently use a wide range of natural language processing (NLP) packages to: implement text classification, identify parts of speech, utilize topic modeling, text summarization, sentiment analysis, information retrieval, and many more applications of NLP.
The book begins with text data collection, web scraping, and the different types of data sources. It explains how to clean and pre-process text data, and offers ways to analyze data with advanced algorithms. You then explore semantic and syntactic analysis of the text. Complex NLP solutions that involve text normalization are covered along with advanced pre-processing methods, POS tagging, parsing, text summarization, sentiment analysis, word2vec, seq2seq, and much more. The book presents the fundamentals necessary for applications of machine learning and deep learning in NLP. This second edition goes over advanced techniques to convert text to features such as Glove, Elmo, Bert, etc. It also includes an understanding of how transformers work, taking sentence BERT and GPT as examples. The final chapters explain advanced industrial applications of NLP with solution implementation and leveraging the power of deep learning techniques for NLP problems. It also employs state-of-the-art advanced RNNs, such as long short-term memory, to solve complex text generation tasks.
After reading this book, you will have a clear understanding of the challenges faced by different industries and you will have worked on multiple examples of implementing NLP in the real world.
You will:

  • Know the core concepts of implementing NLP and various approaches to natural language processing (NLP), including NLP using Python libraries such as NLTK, textblob, SpaCy, Standford CoreNLP, and more
  • Implement text pre-processing and feature engineering in NLP, including advanced methods of feature engineering
  • Understand and implement the concepts of information retrieval, text summarization, sentiment analysis, text classification, and other advanced NLP techniques leveraging machine learning and deep learning

 

商品描述(中文翻譯)

專注於使用 Python 實現端到端的專案，並利用最先進的演算法。本書教您有效地使用各種自然語言處理（NLP）套件來：實現文本分類、識別詞性、利用主題建模、文本摘要、情感分析、資訊檢索，以及許多其他 NLP 應用。

本書從文本數據收集、網頁爬蟲和不同類型的數據來源開始。它解釋了如何清理和預處理文本數據，並提供使用先進演算法分析數據的方法。接著，您將探索文本的語義和句法分析。涵蓋了涉及文本正規化的複雜 NLP 解決方案，以及先進的預處理方法、詞性標註、解析、文本摘要、情感分析、word2vec、seq2seq 等等。本書介紹了在 NLP 中應用機器學習和深度學習所需的基本知識。本第二版涵蓋了將文本轉換為特徵的先進技術，如 Glove、Elmo、Bert 等。它還包括對變壓器如何工作的理解，以句子 BERT 和 GPT 為例。最後幾章解釋了 NLP 的先進工業應用，並實現解決方案，利用深度學習技術的力量來解決 NLP 問題。它還使用最先進的 RNN，如長短期記憶（LSTM），來解決複雜的文本生成任務。

閱讀本書後，您將清楚了解不同產業面臨的挑戰，並且您將在多個實例中實現 NLP 的應用。

您將：


  • 了解實現 NLP 的核心概念及各種自然語言處理（NLP）方法，包括使用 Python 函式庫如 NLTK、textblob、SpaCy、Standford CoreNLP 等進行 NLP

  • 在 NLP 中實現文本預處理和特徵工程，包括先進的特徵工程方法

  • 理解並實現資訊檢索、文本摘要、情感分析、文本分類及其他利用機器學習和深度學習的先進 NLP 技術的概念

 

作者簡介

Akshay Kulkarni is an AI and machine learning evangelist and thought leader. He has consulted with Fortune 500 and global enterprises to drive AI and data science-led strategic transformations. He has a rich experience of building and scaling AI and machine learning businesses and creating significant client impact. Akshay is currently Manager-Data Science & AI at Publicis Sapient where he is part of strategy and transformation interventions through AI. He manages high-priority growth initiatives around data science, works on AI engagements, and applies state-of-the-art techniques. Akshay is a Google Developers Expert-Machine Learning, and is a published author of books on NLP and deep learning. He is a regular speaker at major AI and data science conferences, including Strata, O'Reilly AI Conf, and GIDS. In 2019, he was featured as one of the Top "40 under 40 Data Scientists" in India. In his spare time, he enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.

Adarsha Shivananda is Lead Data Scientist at Indegene's Product and Technology team where he leads a group of analysts who enable predictive analytics and AI features for all of their healthcare software products. They handle multi-channel activities for pharma products and solve real-time problems encountered by pharma sales reps. Adarsha aims to build a pool of exceptional data scientists within the organization and to solve greater health care problems through training programs and staying ahead of the curve. His core expertise involves machine learning, deep learning, recommendation systems, and statistics. Adarsha has worked on data science projects across multiple domains using different technologies and methodologies. Previously, he was part of Tredence Analytics and IQVIA. He lives in Bangalore and loves to read and teach data science.

作者簡介(中文翻譯)

阿克謝·庫爾卡尼 是一位人工智慧和機器學習的推廣者及思想領袖。他曾與《財富》500 強企業及全球企業合作，推動以人工智慧和數據科學為主導的戰略轉型。他在建立和擴展人工智慧及機器學習業務方面擁有豐富的經驗，並為客戶創造了顯著的影響。阿克謝目前擔任 Publicis Sapient 的數據科學與人工智慧經理，參與通過人工智慧進行的策略和轉型干預。他管理與數據科學相關的高優先級增長計劃，參與人工智慧項目，並應用最先進的技術。阿克謝是 Google 開發者專家-機器學習，並且是有關自然語言處理（NLP）和深度學習的書籍的出版作者。他是主要人工智慧和數據科學會議的常規演講者，包括 Strata、O'Reilly AI Conf 和 GIDS。在 2019 年，他被評選為印度「40 位 40 歲以下數據科學家」之一。在空閒時間，他喜歡閱讀、寫作、編碼，並幫助有志於成為數據科學家的朋友。他與家人居住在班加羅爾。

阿達爾莎·希瓦南達 是 Indegene 產品與技術團隊的首席數據科學家，負責領導一組分析師，為其所有醫療保健軟體產品啟用預測分析和人工智慧功能。他們處理製藥產品的多渠道活動，並解決製藥銷售代表所遇到的實時問題。阿達爾莎的目標是在組織內建立一支卓越的數據科學家團隊，並通過培訓計劃解決更大的醫療保健問題，保持領先地位。他的核心專業包括機器學習、深度學習、推薦系統和統計學。阿達爾莎曾在多個領域的數據科學項目中使用不同的技術和方法進行工作。之前，他曾在 Tredence Analytics 和 IQVIA 工作。他居住在班加羅爾，喜歡閱讀和教授數據科學。

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