Python Natural Language Processing Cookbook - Second Edition: Over 60 recipes for building powerful NLP solutions using Python and LLM libraries
Antic, Zhenya, Chakravarty, Saurabh
- 出版商: Packt Publishing
- 出版日期: 2024-09-13
- 售價: $1,720
- 貴賓價: 9.5 折 $1,634
- 語言: 英文
- 頁數: 312
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1803245743
- ISBN-13: 9781803245744
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相關分類:
LangChain、Python、程式語言、Text-mining
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相關主題
商品描述
Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAI
Key Features:
- Leverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI models
- Use LLM-powered agents for custom tasks and real-world interactions
- Gain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMs
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description:
Harness the power of Natural Language Processing to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess.
You'll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you'll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You'll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs.
This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)-fostering trust and transparency in your NLP models.
By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.
What You Will Learn:
- Understand fundamental NLP concepts along with their applications using examples in Python
- Classify text quickly and accurately with rule-based and supervised methods
- Train NER models and perform sentiment analysis to identify entities and emotions in text
- Explore topic modeling and text visualization to reveal themes and relationships within text
- Leverage Hugging Face and OpenAI LLMs to perform advanced NLP tasks
- Use question-answering techniques to handle both open and closed domains
- Apply XAI techniques to better understand your model predictions
Who this book is for:
This updated edition of the Python Natural Language Processing Cookbook is for data scientists, machine learning engineers, and developers with a background in Python. Whether you're looking to learn NLP techniques, extract valuable insights from textual data, or create foundational applications, this book will equip you with basic to intermediate skills. No prior NLP knowledge is necessary to get started. All you need is familiarity with basic programming principles. For seasoned developers, the updated sections offer the latest on transformers, explainable AI, and Generative AI with LLMs.
Table of Contents
- Learning NLP Basics
- Playing with Grammar
- Representing Text - Capturing Semantics
- Classifying Texts
- Getting Started with Information Extraction
- Topic Modeling
- Visualizing Text Data
- Transformers and Their Applications
- Natural Language Understanding
- Generative AI and Large Language Models
商品描述(中文翻譯)
更新內容包括三個新章節，涵蓋變壓器、可解釋的人工智慧（Explainable AI）下的自然語言理解（NLU），以及與 Hugging Face 和 OpenAI 的熱門大型語言模型（LLMs）互動。
主要特色：
- 利用最新的 LLMs，包括 Mistral、Llama 和 OpenAI 模型，使用現成的食譜。
- 使用 LLM 驅動的代理進行自定義任務和現實世界互動。
- 獲得有關變壓器的實用深入知識，以及它們在實現各種自然語言處理（NLP）任務中的角色，使用開源和先進的 LLMs。
- 購買印刷版或 Kindle 書籍可獲得免費 PDF 電子書。
書籍描述：
利用自然語言處理的力量，克服現實世界的文本分析挑戰，這本以食譜為基礎的路線圖由兩位經驗豐富的 NLP 專家撰寫，他們在轉型各行各業方面擁有豐富的經驗。
您將能夠充分利用最新的 NLP 進展，包括大型語言模型（LLMs），並通過 Hugging Face 的變壓器發揮其能力。通過一系列實作食譜，您將掌握提取實體和可視化文本數據等基本技術。作者將專業指導您建立情感分析、主題建模和問答的管道，使用流行的庫如 spaCy、Gensim 和 NLTK。您還將學習如何實施 RAG 管道，利用 LLMs 從文本語料庫中提取精確答案。
本第二版擴展了您的技能，新增了有關尖端 LLMs（如 GPT-4）、自然語言理解（NLU）和可解釋的人工智慧（XAI）的章節，促進您對 NLP 模型的信任和透明度。
在本書結束時，您將具備應用先進文本處理技術的能力，使用預訓練的變壓器模型，建立自定義 NLP 管道，從文本數據中提取有價值的見解，以推動明智的決策。
您將學到的內容：
- 理解基本的 NLP 概念及其應用，並使用 Python 的範例。
- 使用基於規則和監督的方法快速準確地分類文本。
- 訓練 NER 模型並執行情感分析，以識別文本中的實體和情感。
- 探索主題建模和文本可視化，以揭示文本中的主題和關係。
- 利用 Hugging Face 和 OpenAI 的 LLMs 執行先進的 NLP 任務。
- 使用問答技術處理開放和封閉領域。
- 應用 XAI 技術以更好地理解模型預測。
本書適合對象：
這本更新版的 Python 自然語言處理食譜適合數據科學家、機器學習工程師和具備 Python 背景的開發者。無論您是想學習 NLP 技術、從文本數據中提取有價值的見解，還是創建基礎應用，本書將為您提供從基礎到中級的技能。開始時不需要具備先前的 NLP 知識，只需對基本編程原則有一定的熟悉度。對於經驗豐富的開發者，更新的部分提供了有關變壓器、可解釋的人工智慧和使用 LLMs 的生成式人工智慧的最新資訊。
目錄：
- 學習 NLP 基礎
- 玩轉語法
- 表示文本 - 捕捉語義
- 文本分類
- 開始進行信息提取
- 主題建模
- 可視化文本數據
- 變壓器及其應用
- 自然語言理解
- 生成式人工智慧和大型語言模型
