Book Image

Mastering NLP from Foundations to LLMs

By : Lior Gazit, Meysam Ghaffari
Book Image

Mastering NLP from Foundations to LLMs

By: Lior 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)

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...