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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

By : Gazit, Meysam Ghaffari
4.9 (24)
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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

4.9 (24)
By: Gazit, Meysam Ghaffari

Overview of this 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.
Table of Contents (14 chapters)
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Reviewing a simple LangChain setup in a Jupyter notebook

We are now ready to set up a complete pipeline that can later be lent to various NLP applications.

Refer to the Ch8_Setting_Up_LangChain_Configurations_and_Pipeline.ipynb notebook. This notebook implements the LangChain framework. We will walk through it step by step, explaining the different building blocks. We chose a simple use case here, as the main point of this code is to show how to set up a LangChain pipeline.

In this scenario, we are in the healthcare sector. We have many care givers; each has many patients they may see. The physician in chief made a request on behalf of all the physicians in the hospital to be able to use a smart search across their notes. They heard about the new emerging capabilities with LLMs, and they would like to have a tool where they can search within the medical reports they wrote.

For instance, one physician said the following:

I often come across research that may be...

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