Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python
Gazit, Lior, Ghaffari, Meysam
- 出版商: Packt Publishing
- 出版日期: 2024-04-26
- 售價: $1,920
- 貴賓價: 9.5 折 $1,824
- 語言: 英文
- 頁數: 340
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1804619183
- ISBN-13: 9781804619186
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相關分類:
LangChain、Python、程式語言、Text-mining
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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)
增強您在現代框架(如LangChain)下的自然語言處理(NLP)能力,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:
- 學習如何使用Python構建以NLP、LLMs、RAGs和GPT為重點的解決方案
- 掌握嵌入技術和機器學習原理,應用於實際應用
- 理解NLP和深度學習設計的數學基礎
- 購買印刷版或Kindle電子書,可獲得免費PDF電子書
書籍描述:
您想精通自然語言處理(NLP),但不知道從何開始?本書將為您提供正確的起點。由機器學習和NLP領域的專家撰寫,《從基礎到LLMs的NLP精通》深入介紹了相關技術。從機器學習(ML)的數學基礎開始,您將逐步深入研究高級NLP應用,如大型語言模型(LLMs)和人工智能應用。您將掌握線性代數、優化、概率和統計等基礎知識,這些對於理解和實現機器學習和NLP算法至關重要。您還將探索通用的機器學習技術,並了解它們與NLP的關聯。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進行分析的方法,並了解如何進行文本分類。除此之外,您還將獲得完整的Python代碼範例。
通過本書,您將深入討論LLMs的理論、設計和應用等高級主題,並獲得專家對NLP未來趨勢的觀點。您還將通過解決實際的NLP業務問題和解決方案來增強您的實踐能力。
您將學到什麼:
- 掌握機器學習和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,以及在人工智能各個應用中的實現
- 探索NLP的見解、趨勢和專家對其未來方向和潛力的意見
本書適合對深度學習和機器學習進行研究的人、NLP從業者、機器學習/NLP教育工作者和STEM學生。在項目中處理文本數據的專業人士也可以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工作知識將有助於您充分利用本書。
目錄大綱
- Navigating the NLP Landscape: A comprehensive introduction
- Mastering Linear Algebra, Probability, and Statistics for Machine Learning and NLP
- Unleashing Machine Learning Potentials in NLP
- Streamlining Text Preprocessing Techniques for Optimal NLP Performance
- Empowering Text Classification: Leveraging Traditional Machine Learning Techniques
- Text Classification Reimagined: Delving Deep into Deep Learning Language Models
- Demystifying Large Language Models: Theory, Design, and Langchain Implementation
- Accessing the Power of Large Language Models: Advanced Setup and Integration with RAG
- Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs
- Riding the Wave: Analyzing Past, Present, and Future Trends Shaped by LLMs and AI
- Exclusive Industry Insights: Perspectives and Predictions from World Class Experts
目錄大綱(中文翻譯)
導航 NLP 領域: 全面介紹
精通線性代數、機率和統計: 機器學習和 NLP
釋放 NLP 中的機器學習潛力
優化 NLP 效能的文本預處理技術
強化文本分類: 利用傳統機器學習技術
重新想像文本分類: 深入探索深度學習語言模型
揭秘大型語言模型: 理論、設計和 Langchain 實現
利用大型語言模型的強大功能: 高級設置和與 RAG 的整合
探索前沿: 基於 LLM 的高級應用和創新
乘風破浪: 分析 LLM 和 AI 塑造的過去、現在和未來趨勢
獨家行業見解: 世界級專家的觀點和預測