Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python
暫譯: 掌握自然語言處理：從基礎到大型語言模型，應用進階規則基礎技術於大型語言模型，並使用 Python 解決實際商業問題

Gazit, Lior, Ghaffari, Meysam

Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python

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商品描述

Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends

Key Features

  • Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT
  • Master embedding techniques and machine learning principles for real-world applications
  • Understand the mathematical foundations of NLP and deep learning designs
  • Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Do you want to master Natural Language Processing (NLP) but don't know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you'll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You'll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You'll also explore general machine learning techniques and find out how they relate to NLP. Next, you'll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You'll get all of this and more along with complete Python code samples.

By the end of the book, the advanced topics of LLMs' theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You'll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.

What you will learn

  • Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python
  • Model and classify text using traditional machine learning and deep learning methods
  • Understand the theory and design of LLMs and their implementation for various applications in AI
  • Explore NLP insights, trends, and expert opinions on its future direction and potential

Who this book is for

This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.

商品描述(中文翻譯)

增強您在自然語言處理（NLP）方面的能力，使用像 LangChain 這樣的現代框架，探索數學基礎和程式碼範例，並獲得對當前和未來趨勢的專家見解。

主要特點

- 學習如何構建以 Python 驅動的解決方案，重點關注 NLP、LLMs、RAGs 和 GPT
- 精通嵌入技術和機器學習原則，以應用於實際情境
- 理解 NLP 和深度學習設計的數學基礎
- 購買印刷版或 Kindle 書籍可獲得免費 PDF 電子書

書籍描述

您想掌握自然語言處理（NLP），但不知道從何開始嗎？這本書將為您提供良好的起點。由機器學習和 NLP 領域的領導者撰寫的《從基礎到 LLMs 的 NLP 精通》提供了技術的深入介紹。從機器學習（ML）的數學基礎開始，您將逐步進入大型語言模型（LLMs）和 AI 應用等高級 NLP 應用。您將掌握線性代數、優化、概率和統計，這些都是理解和實現機器學習和 NLP 算法的必要知識。您還將探索一般的機器學習技術，並了解它們與 NLP 的關係。接下來，您將學習如何預處理文本數據，探索清理和準備文本以進行分析的方法，並理解如何進行文本分類。您將獲得所有這些內容以及完整的 Python 程式碼範例。

在書籍結束時，將討論 LLMs 的理論、設計和應用的高級主題，以及 NLP 的未來趨勢，並包含專家的意見。您還將通過處理實際的 NLP 商業問題和解決方案來加強您的實踐技能。

您將學到什麼

- 精通機器學習和 NLP 的數學基礎，實現文本數據預處理和分析的高級技術，設計 Python 中的 ML-NLP 系統
- 使用傳統機器學習和深度學習方法對文本進行建模和分類
- 理解 LLMs 的理論和設計及其在各種 AI 應用中的實現
- 探索 NLP 的見解、趨勢以及專家對其未來方向和潛力的意見

本書適合誰

本書適合深度學習和機器學習研究人員、NLP 實踐者、ML/NLP 教育工作者以及 STEM 學生。從事文本數據相關項目的專業人士也會在本書中找到大量有用的信息。對機器學習有初步了解並具備基本的 Python 工作知識將幫助您充分利用本書。

目錄大綱

  1. Navigating the NLP Landscape: A comprehensive introduction
  2. Mastering Linear Algebra, Probability, and Statistics for Machine Learning and NLP
  3. Unleashing Machine Learning Potentials in NLP
  4. Streamlining Text Preprocessing Techniques for Optimal NLP Performance
  5. Empowering Text Classification: Leveraging Traditional Machine Learning Techniques
  6. Text Classification Reimagined: Delving Deep into Deep Learning Language Models
  7. Demystifying Large Language Models: Theory, Design, and Langchain Implementation
  8. Accessing the Power of Large Language Models: Advanced Setup and Integration with RAG
  9. Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs
  10. Riding the Wave: Analyzing Past, Present, and Future Trends Shaped by LLMs and AI
  11. Exclusive Industry Insights: Perspectives and Predictions from World Class Experts

目錄大綱(中文翻譯)


  1. Navigating the NLP Landscape: A comprehensive introduction

  2. Mastering Linear Algebra, Probability, and Statistics for Machine Learning and NLP

  3. Unleashing Machine Learning Potentials in NLP

  4. Streamlining Text Preprocessing Techniques for Optimal NLP Performance

  5. Empowering Text Classification: Leveraging Traditional Machine Learning Techniques

  6. Text Classification Reimagined: Delving Deep into Deep Learning Language Models

  7. Demystifying Large Language Models: Theory, Design, and Langchain Implementation

  8. Accessing the Power of Large Language Models: Advanced Setup and Integration with RAG

  9. Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs

  10. Riding the Wave: Analyzing Past, Present, and Future Trends Shaped by LLMs and AI

  11. Exclusive Industry Insights: Perspectives and Predictions from World Class Experts

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