Mastering NLP from Foundations to LLMs
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Mastering NLP from Foundations to LLMs

Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python

About the Book

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.

About the Author

Packt Publishing Ltd
Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

Table of Contents

  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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