This book provides an in-depth introduction to natural language processing (NLP) techniques, starting with the mathematical foundations of machine learning and working up to advanced NLP applications such as Larg Language Models (LLMs) and AI applications. The second chapter covers linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. The third chapter delves into general machine learning techniques and relates them to NLP. The forth chapter covers preprocessing of text data, including methods for cleaning and preparing text for analysis. The fifth and sixth chapters covers text classification, which is the task of assigning a label or category to a piece of text based on its content. The seventh through ninth chapters discuss the advanced topics of LLMs’ theory, design, and applications. The tenth chapter looks ahead to future trends in NLP, and the eleventh chapter features expert opinions on the future of the field. This book also covers some of the sample real world NLP business problems and solutions.