Generative AI with Python : The Developer's Guide to Pretrained LLMs, Vector Databases, Retrieval-Augmented Generation, and Agentic Systems
Language: English
Published by Rheinwerk Verlag Gmbh Okt 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Neuware - Your guide to generative AI with Python is here! Start with an introduction to generative AI, NLP models, LLMs, and LMMs-and then dive into pretrained models with Hugging Face. Work with LLMs using Python with the help of tools like OpenAI and LangChain. Get step-by-step instructions for working with vector databases and using retrieval-augmented generation. With information on agentic systems and AI application deployment, this guide gives you all you need to become an AI master!Highlights:1) Natural language processing (NLP) models2) Large language models (LLMs)3) Pretrained models4) Prompt engineering5) Vector databases6) Retrieval-augmented generation (RAG)7) Agentic systems8) OpenAI9) LangChain10) Hugging Face11) crewAI12) AG2.
Seller Inventory # 9781493226900
- Title
- Generative AI with Python : The Developer's Guide to Pretrained LLMs, Vector Databases, Retrieval-Augmented Generation, and Agentic Systems
- Author
- Bert Gollnick
- Publisher
- Rheinwerk Verlag Gmbh Okt 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1493226908
- ISBN 13
- 9781493226900
- Item weight
- 690 grams
- Dimensions
- 252x177x22 mm
Your guide to generative AI with Python is here! Start with an introduction to generative AI, NLP models, LLMs, and LMMs and then dive into pretrained models with Hugging Face. Work with LLMs using Python with the help of tools like OpenAI and LangChain. Get step-by-step instructions for working with vector databases and using retrieval-augmented generation. With information on agentic systems and AI application deployment, this guide gives you all you need to become an AI master!
Highlights:
1) Natural language processing (NLP) models
2) Large language models (LLMs)
3) Pretrained models
4) Prompt engineering
5) Vector databases
6) Retrieval-augmented generation (RAG)
7) Agentic systems
8) OpenAI
9) LangChain
10) Hugging Face
11) crewAI
12) AutoGen
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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