About the Author xv
About the Technical Reviewer xvii
Acknowledgments xix
Introduction xxi
Chapter 1: Evolution and Significance of Large Language Models 1
Chapter 2: What Are Large Language Models? 59
Chapter 3: Python for LLMs 101
Chapter 4: Python and Other Programming Approaches 165
Chapter 5: Basic Overview of the Components of the LLM Architectures 199
Chapter 6: Applications of LLMs in Python 263
Chapter 7: Harnessing Python 3.11 and Python Libraries for LLM Development 303
Index 369
Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today's computational world. This book is an introductory guide to NLP and LLMs with Python programming.
The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components.
You'll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You'll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots.
In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs.
Data analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.