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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
Author Profile Icon Lior Gazit
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

Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs

In the rapidly evolving landscape of natural language processing (NLP), large language models (LLMs) have marked a revolutionary step forward, reshaping how we interact with information, automate processes, and derive insights from vast data pools. This chapter represents the culmination of our journey through the emergence and development of NLP methods. It is here that the theoretical foundations laid in previous chapters converge with practical, cutting-edge applications, illuminating the remarkable capabilities of LLMs when harnessed with the right tools and techniques.

We delve into the most recent and thrilling advancements in LLM applications, presented through detailed Python code examples designed for hands-on learning. This approach not only illustrates the power of LLMs but also equips you with the skills to implement these technologies in real-world scenarios. The subjects covered in this chapter...

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