The book provides an overview of central concepts and techniques of Large Language Models (LLMs) such as ChatGPT and demonstrates the potential of both open-source and closed-source models. It explains how Large Language Models work and how they can be utilized for Natural Language Processing (NLP) tasks. It is also accessible to interested non-data scientists with Python knowledge. Topics include the ChatGPT API, prompt engineering, chatbot personas, and cloud deployment, with a discussion on GPT-4 as well.

Large Language Models like ChatGPT exhibit remarkable capabilities, but their size and complexity deter many practitioners from implementing them in their own applications. In this introduction, data scientist and AI entrepreneur Sinan Ozdemir removes these obstacles and provides a guide for using LLMs to solve practical NLP problems. Sinan Ozdemir has compiled everything you need to get started, even if you have no prior experience with LLMs: step-by-step instructions, best practices, real-world case studies, exercises, and much more. At the same time, he offers insights into how LLMs function to assist you in selecting models, data formats, and parameters. On the author's accompanying website, you will find additional resources, including sample datasets and code for working with open-source and closed-source LLMs.