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.
Applied Generative AI for Beginners 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.
Whether you’re a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights.
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 and LLMs.
Sharath B L –
“Generative AI for Beginners” is an excellent resource for newcomers to the field, offering clear explanations of complex AI concepts and practical examples. It’s particularly useful for those in creative industries, blending technical knowledge with innovative applications. The book’s accessible approach makes it a valuable addition to any beginner’s learning toolkit.
Eric Marthinsen –
This book barely discusses applications of generative AI. It certainly isn’t for beginners. And, it contains no practical knowledge.This book was poorly written and even more poorly edited. Despite being for beginners, the book would often use more advanced terminology without any explanation. What explanations there are were incomprehensible. A rudimentary code snippet on using the OpenAI API randomly show up in the middle of the chapter on LLM Operations. One section seems to have been copied from a Microsoft site. Another section appears to be from a blog, since it references the author’s “last update”.Overall, this book is just a soup of LLM-related jargon and marketing material. It’s all noise and no signal. My knowledge of LLMs and generative AI didn’t increase from reading this book. In fact, I may well know less now for having read it.
Nickhil –
This book had a thorough look into generative AI and it talked about different technologies such as LLMS like ChatGPT. This book gives you more than enough knowledge to understand how generative AI works.