000 03651nam a22005295i 4500
001 979-8-8688-0205-8
003 DE-He213
005 20251030111742.0
007 cr nn 008mamaa
008 240323s2024 xxu| s |||| 0|eng d
020 _a9798868802058
_9979-8-8688-0205-8
024 7 _a10.1007/979-8-8688-0205-8
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
100 1 _aKansal, Aarushi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_973872
245 1 0 _aBuilding Generative AI-Powered Apps
_h[electronic resource] :
_bA Hands-on Guide for Developers /
_cby Aarushi Kansal.
250 _a1st ed. 2024.
264 1 _aBerkeley, CA :
_bApress :
_bImprint: Apress,
_c2024.
300 _aXI, 170 p. 42 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 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: .
520 _aGenerative 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?
650 0 _aArtificial intelligence.
_958441
650 0 _aMachine learning.
_955059
650 0 _aPython (Computer program language).
_964608
650 1 4 _aArtificial Intelligence.
_958441
650 2 4 _aMachine Learning.
_955059
650 2 4 _aPython.
_947553
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9798868802041
776 0 8 _iPrinted edition:
_z9798868802065
776 0 8 _iPrinted edition:
_z9798868806247
856 4 0 _uhttps://doi.org/10.1007/979-8-8688-0205-8
912 _aZDB-2-CWD
912 _aZDB-2-SXPC
999 _c58621
_d58621