Natural Language Processing with Flair: A practical guide to understanding and solving NLP problems with Flair

Magajna, Tadej

  • 出版商: Packt Publishing
  • 出版日期: 2022-04-29
  • 售價: $1,500
  • 貴賓價: 9.5$1,425
  • 語言: 英文
  • 頁數: 200
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1801072310
  • ISBN-13: 9781801072311
  • 相關分類: Text-mining
  • 立即出貨 (庫存=1)

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商品描述

Learn how to solve practical NLP problems with the Flair Python framework, train sequence labeling models, work with text classifiers and word embeddings, and much more through hands-on practical exercises

Key Features

- Backed by the community and written by an NLP expert
- Get an understanding of basic NLP problems and terminology
- Solve real-world NLP problems with Flair with the help of practical hands-on exercises

Book Description

Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings.

Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production.

By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you'll be able to solve them with Flair.

What you will learn

- Gain an understanding of core NLP terminology and concepts
- Get to grips with the capabilities of the Flair NLP framework
- Find out how to use Flair's state-of-the-art pre-built models
- Build custom sequence labeling models, embeddings, and classifiers
- Learn about a novel text classification technique called TARS
- Discover how to build applications with Flair and how to deploy them to production

Who this book is for

This Flair NLP book is for anyone who wants to learn about NLP through one of the most beginner-friendly, yet powerful Python NLP libraries out there. Software engineering students, developers, data scientists, and anyone who is transitioning into NLP and is interested in learning about practical approaches to solving problems with Flair will find this book useful. The book, however, is not recommended for readers aiming to get an in-depth theoretical understanding of the mathematics behind NLP. Beginner-level knowledge of Python programming is required to get the most out of this book.

商品描述(中文翻譯)

學習如何使用Flair Python框架解決實際的自然語言處理(NLP)問題,通過實際操作練習來訓練序列標記模型、使用文本分類器和詞嵌入等等。

主要特點:
- 得到社區支持,由NLP專家撰寫
- 瞭解基本的NLP問題和術語
- 通過實際操作練習來解決實際的NLP問題

書籍描述:
Flair是一個易於理解的自然語言處理(NLP)框架,旨在促進訓練和分發最先進的NLP模型,用於命名實體識別、詞性標註和文本分類。Flair還是一個文本嵌入庫,用於結合不同類型的嵌入,例如文檔嵌入、Transformer嵌入和提出的Flair嵌入。

《使用Flair進行自然語言處理》採用實踐方法來解釋和解決實際的NLP問題。您將首先安裝Flair並了解基本的NLP概念和術語。通過實際操作練習,您將探索Flair的廣泛功能,例如序列標記、文本分類和詞嵌入。隨著進一步的學習,您將訓練自己的序列標記和文本分類模型,並學習如何使用超參數調整來選擇合適的訓練參數。您將通過一種新的文本分類技術TARS來了解一次性和少次性學習的思想。最後,您將通過實際操作練習解決幾個實際的NLP問題,並學習如何將Flair模型部署到生產環境中。

通過閱讀本書,您將對典型的NLP問題有深入的了解,並能夠使用Flair解決這些問題。

您將學到:
- 瞭解核心NLP術語和概念
- 掌握Flair NLP框架的能力
- 瞭解如何使用Flair的最先進的預建模型
- 構建自定義的序列標記模型、嵌入和分類器
- 學習一種名為TARS的新型文本分類技術
- 發現如何使用Flair構建應用程序並將其部署到生產環境中

本書適合對NLP感興趣並希望通過最友好且功能強大的Python NLP庫之一來學習NLP的任何人。軟件工程學生、開發人員、數據科學家以及正在轉向NLP並有興趣學習使用Flair解決問題的人會發現本書很有用。然而,不建議那些希望深入理解NLP背後數學原理的讀者閱讀本書。需要初級水平的Python編程知識才能充分利用本書。

目錄大綱

1. Introduction to Flair
2. Flair Base Types
3. Embeddings in Flair
4. Sequence Tagging
5. Training Sequence Labeling Models
6. Hyperparameter Optimization in Flair
7. Training Your Own Embeddings
8. Text Classification in Flair
9. Deploying and Using Models in Production
10. Hands-on exercise – Building a trading bot with Flair

目錄大綱(中文翻譯)

1. Flair 簡介
2. Flair 基本類型
3. Flair 中的嵌入
4. 序列標記
5. 訓練序列標記模型
6. Flair 中的超參數優化
7. 訓練自己的嵌入
8. Flair 中的文本分類
9. 在生產環境中部署和使用模型
10. 實戰練習 - 使用 Flair 建立交易機器人