
Sách Applied Generative AI for Beginners Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs (sách keo gáy, bìa mềm)
This book provides a deep dive into the world of
generative AI, covering everything from the basics of neural networks to
the intricacies of large language models like ChatGPT and Google Bard.
It serves as a one-stop resource for anyone interested in understanding
and applying this transformative technology and is particularly aimed at
those just getting started with generative AI.
This book is
structured around detailed chapters that will guide you from
foundational knowledge to practical implementation. It starts with an
introduction to generative AI and its current landscape, followed by an
exploration of how the evolution of neural networks led to the
development of large language models. The book then delves into specific
architectures like ChatGPT and Google Bard, offering hands-on
demonstrations for implementation using tools like Sklearn. You’ll also
gain insight into the strategic aspects of implementing generative AI in
an enterprise setting, with the authors covering crucial topics such as
LLMOps, technology stack selection, and in-context learning. The latter
part of the book explores generative AI for images and provides
industry-specific use cases, making it a comprehensive guide for
practical application in various domains.
What You Will Learn
•
Gain a solid understanding of generative AI, starting from the basics
of neural networks and progressing to complex architectures like ChatGPT
and Google Bard
• Implement large language models using Sklearn, complete with code examples and best practices for real-world application
• Learn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selection
•
Understand how generative AI can be applied across various industries,
from healthcare and marketing to legal compliance through detailed use
cases and actionable insights
Who This Book Is For
Data scientists, AI practitioners, Researchers and software engineers interested in generative AI & LLMs
Categories:Computers - Artificial Intelligence (AI)
Year:2023
Edition:1
Language:english
Pages:221