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)

Accessing the Power of Large Language Models: Advanced Setup and Integration with RAG

In this dynamic era of Artificial Intelligence (AI) and Machine Learning (ML), understanding the vast assortment of available resources and learning how to utilize them effectively is vital. Large Language Models (LLMs) such as GPT-4 have revolutionized the field of Natural Language Processing (NLP) by showcasing unprecedented performance in diverse tasks, from content generation to complex problem-solving. Their immense potential extends not only to understanding and generating human-like text but also to bridging the gap between machines and humans, in terms of communication and task automation. Embracing the practical applications of LLMs can empower businesses, researchers, and developers to create more intuitive, intelligent, and efficient systems that cater to a wide range of requirements. This chapter offers a guide to setting up access to LLMs, walking you through using them and building pipelines...