03651nam a22005295i 4500 979-8-8688-0205-8 DE-He213 20251030111742.0 cr nn 008mamaa 240323s2024 xxu| s |||| 0|eng d 9798868802058 979-8-8688-0205-8 10.1007/979-8-8688-0205-8 doi Q334-342 TA347.A78 UYQ bicssc COM004000 bisacsh UYQ thema Kansal, Aarushi. author. aut http://id.loc.gov/vocabulary/relators/aut 73872 Building Generative AI-Powered Apps [electronic resource] : A Hands-on Guide for Developers / by Aarushi Kansal. 1st ed. 2024. Berkeley, CA : Apress : Imprint: Apress, 2024. XI, 170 p. 42 illus. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Chapter 1: Introduction to Generative AI -- Chapter 2: LangChain + AI -- Using Chains -- Chapter 3: AI + Embeddings -- Chapter 4: AI + Text at Scale -- Chapter 5: AI and Audio -- Chapter 6: Finetuning GPT -- Chapter 7: Monitoring -- Chapter 8: UI + UX -- Appendix A: . Generative AI has gone beyond the responsibility of researchers and data scientists and is being used by production engineers. However, there is a lot of confusion where to get started when building an end-to-end app with generative AI. This book consolidates core models, frameworks, and tools into a single source of knowledge. By providing hands-on examples, the book takes you through the generative AI ecosystem to build applications for production. The book starts with a brief and accessible introduction to transformer models before delving into some of the most popular large language models and diffusions models (image generation). These models are the foundations of both AI and your potential new apps. You will then go through various tools available to work with these models, starting with Langchain, a framework to develop foundational models, which is the next building block you should grasp after understanding generative AI models. The next chapters cover databases, caching, monitoring, etc., which are the topics necessary to build larger-scale applications. Real-world examples using these models and tools are included. By the end of this book, you should be able to build end-to-end apps that are powered by generative AI. You also should be able to apply the tools and techniques taught in this book to your use cases and business. What You Will Learn What is Generative AI? What is ChatGPT and GPT4? What are language models and diffusions models? How do we deploy LangChain and HuggingFace? Artificial intelligence. 58441 Machine learning. 55059 Python (Computer program language). 64608 Artificial Intelligence. 58441 Machine Learning. 55059 Python. 47553 SpringerLink (Online service) Springer Nature eBook Printed edition: 9798868802041 Printed edition: 9798868802065 Printed edition: 9798868806247 https://doi.org/10.1007/979-8-8688-0205-8 ZDB-2-CWD ZDB-2-SXPC 58621 58621