Preface

This book provides an in-depth introduction to natural language processing (NLP) techniques, starting with the mathematical foundations of machine learning (ML) and working up to advanced NLP applications such as large language models (LLMs) and AI applications. As part of your learning experience, you’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing ML and NLP algorithms. You’ll also explore general ML techniques and find out how they relate to NLP. The preprocessing of text data, including methods for cleaning and preparing text for analysis, will follow, right before you learn how to perform text classification, which is the task of assigning a label or category to a piece of text based on its content. The advanced topics of LLMs’ theory, design, and applications will be discussed toward the end of the book, as will the future trends in NLP, which will feature expert opinions on the future of the field. To strengthen your practical skills, you’ll also work on mocked real-world NLP business problems and solutions.