Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented GenerationКНИГИ » ПРОГРАММИНГ
Название: Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation, and Agentic Systems Автор: Bert Gollnick Издательство: Rheinwerk Publishing Год: 2025 Страниц: 392 Язык: английский Формат: epub (true) Размер: 10.1 MB
Your guide to Generative AI with Python is here! Start with an introduction to generative AI, NLP models, LLMs, and LMMs—and then dive into pretrained models with Hugging Face. Work with LLMs using Python with the help of tools like OpenAI and LangChain. Get step-by-step instructions for working with vector databases and using retrieval-augmented generation. With information on agentic systems and AI application deployment, this guide gives you all you need to become an AI master!
The primary objective of this book is to guide you through the frontiers of this dynamic field, with special attention to large language models (LLMs), the nuanced art of prompt engineering, the utility of vector databases, innovative processes of retrieval-augmented generation (RAG), and the up-and-coming topic of agentic systems.
LLMs have revolutionized the way we interact with text-based AIs. LLMs unlock unparalleled capabilities in language understanding and generation. Well dive into the architectures of these models, dissecting how they learn from massive corpora of data to produce human-like text. Then, we’ll examine prompt engineering, an essential skill in the age of LLMs. You’ll learn how to craft prompts that efficiently navigate the models’ knowledge and capabilities.
Vector databases present the next leap in organizing and retrieving data. Understanding this technology is key to working with high-dimensional data and building systems that are capable of rapid and relevant information access. We’ll explore the concept behind vector databases, their design and function, and how they pave the way for sophisticated AI applications.
The concept of RAG bridges the gap between retrieval of relevant information and on-the-fly text generation. RAG systems mark a significant milestone in AI development, assisting models in producing more accurate, more informed content. The chapter dedicated to RAG will offer an in-depth look at its mechanisms and at integrating this technique into your generative AI applications.
Highlights:
1) Natural language processing (NLP) models 2) Large language models (LLMs) 3) Pretrained models 4) Prompt engineering 5) Vector databases 6) Retrieval-augmented generation (RAG) 7) Agentic systems 8) OpenAI 9) LangChain 10) Hugging Face 11) crewAI 12) AG2
Prerequisites: What You Should Already Know: Before diving into the riveting world of Generative AI with Python, let’s check a few prerequisites to ensure a smooth journey. First, in terms of mandatory requirements, a firm grasp of Python programming is essential; you should be comfortable with the following tasks:
• Writing functions • Creating and manipulating different data structures like lists and dictionaries • Writing loops, mainly for-loops • Using libraries like NumPy and Pandas
Ideally, but not mandatory, you already have a foundational understanding of Machine Learning (ML) concepts, such as training models and working with datasets. Familiarity with basic statistics and linear algebra will also be beneficial, as they underpin many AI algorithms. Although the book will cover the necessary theory behind generative AI, previous exposure to neural networks and Deep Learning frameworks like TensorFlow or PyTorch will help you navigate the more advanced topics more easily. If these prerequisites sound like languages you speak, you’re well equipped to embark on our thrilling voyage through the seas of generative AI landscapes.
Target Audience: This book is designed for a wide array of readers, ranging from software developers and data scientists to students and researchers interested in Generative AI. A certain amount of coding background is expected. If you have a basic understanding of Python programming and a keen interest in AI, especially in the field of generative AI models, this book will serve you well. The book’s content is tailored to engage both novices taking their first steps into the world of generative AI and seasoned professionals seeking to refine their skills and knowledge. Our practical examples and thorough explanations will help you grasp the concepts and techniques essential to developing and applying generative AI systems. Whether you’re looking to innovate in your field, embarking on an academic endeavor, or simply pursuing a fascination with AI, this book hopes to serve as an invaluable resource on your journey.
Скачать Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation
Навигация
Вход на сайт
Реклама
Generative AI with Python: The Developer’s Guide to Pretrained LLMs, Vector Databases, Retrieval Augmented Generation 
