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Mastering NLP from Foundations to LLMs

You're reading from   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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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781804619186
Length 340 pages
Edition 1st Edition
Languages
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Authors (2):
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Meysam Ghaffari Meysam Ghaffari
Author Profile Icon Meysam Ghaffari
Meysam Ghaffari
Lior Gazit Lior Gazit
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Lior Gazit
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Navigating the NLP Landscape: A Comprehensive Introduction 2. Chapter 2: Mastering Linear Algebra, Probability, and Statistics for Machine Learning and NLP FREE CHAPTER 3. Chapter 3: Unleashing Machine Learning Potentials in Natural Language Processing 4. Chapter 4: Streamlining Text Preprocessing Techniques for Optimal NLP Performance 5. Chapter 5: Empowering Text Classification: Leveraging Traditional Machine Learning Techniques 6. Chapter 6: Text Classification Reimagined: Delving Deep into Deep Learning Language Models 7. Chapter 7: Demystifying Large Language Models: Theory, Design, and Langchain Implementation 8. Chapter 8: Accessing the Power of Large Language Models: Advanced Setup and Integration with RAG 9. Chapter 9: Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs 10. Chapter 10: Riding the Wave: Analyzing Past, Present, and Future Trends Shaped by LLMs and AI 11. Chapter 11: Exclusive Industry Insights: Perspectives and Predictions from World Class Experts 12. Index 13. Other Books You May Enjoy

Exclusive Industry Insights: Perspectives and Predictions from World Class Experts

As the journey of this book unfolds, exploring the vast expanse of natural language processing (NLP) and large language models (LLMs), we arrive at a pivotal juncture in Chapter 11. This chapter is not just a culmination of the themes and discussions that preceded it but also a bridge to the untapped potential and imminent challenges that lie ahead in the realm of NLP and LLMs. Our endeavor through the chapters has been to chart the evolution of NLP from its foundational concepts to the architectural marvels of LLMs, dissecting the intricacies of machine learning (ML) strategies, data preprocessing, model training, and the practical applications transforming industries and societal interactions.

The motivation for this chapter stems from an acute recognition of the pace at which NLP and LLM technologies are evolving and the multifaceted impact they wield on the fabric of our digital society. As we...

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