000 02197 a2200217 4500
005 20250826175654.0
020 _a9798868805912
082 _a006.3 KUL
100 _aKulkarni, Akshay
245 _aApplied Generative AI for Beginners : Practical Knowledge on Diffusion Models, ChatGPT, and Other LLMs
260 _bApress
_c2023
_aNew York
300 _a212
520 _aThis 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.
650 _aArtificial Intelligence
650 _aBeginners
650 _aChatGPT
700 _aShivananda, Adarsha
700 _aKulkarni, Anoosh
700 _aGudivada, Dilip
942 _cBK
_2ddc
999 _c51183
_d51183