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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Navigating the NLP Landscape: A Comprehensive Introduction FREE CHAPTER 2. Chapter 2: Mastering Linear Algebra, Probability, and Statistics for Machine Learning and NLP 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

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Mastering-NLP-from-Foundations-to-LLMs If there’s an update to the code, it will be updated in the GitHub repository.

Throughout the book we review complete code notebooks that represent solutions on a professional industry level:

Chapter

Notebook Name

4

Ch4_Preprocessing_Pipeline.ipynb

Ch4_NER_and_POS.ipynb

5

Ch5_Text_Classification_Traditional_ML.ipynb

6

Ch6_Text_Classification_DL.ipynb

8

Ch8_Setting_Up_Close_Source_and_Open_Source_LLMs.ipynb

Ch8_Setting_Up_LangChain_Configurations_and_Pipeline.ipynb

9

Ch9_Advanced_LangChain_Configurations_and_Pipeline.ipynb

Ch9_Advanced_Methods_with_Chains.ipynb

Ch9_Completing_a_Complex_Analysis_with_a_Team_of_LLM_Agents.ipynb

Ch9_RAGLlamaIndex_Prompt_Compression.ipynb

Ch9_Retrieve_Content_from_a_YouTube_Video_and_Summarize.ipynb

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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