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) AG2
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Bert Gollnick is a senior data scientist, specializing in renewable energies. For many years, he has taught courses about data science and machine learning, and more recently, about generative AI and natural language processing. Bert studied aeronautics at the Technical University of Berlin and economics at the University of Hagen. His main areas of interest are machine learning and data science.
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