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)

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...