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Generative AI on Google Cloud with LangChain. Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase

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Generative AI on Google Cloud with LangChain. Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase - okladka książki

Generative AI on Google Cloud with LangChain. Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase - okladka książki

Generative AI on Google Cloud with LangChain. Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase - audiobook MP3

Generative AI on Google Cloud with LangChain. Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase - audiobook CD

Autorzy:
Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei, Harrison Chase
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
306
Dostępne formaty:
     PDF
     ePub
The rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value. Written by three distinguished Google AI engineers and LangChain contributors who have shaped Google Cloud’s integration with LangChain and implemented AI solutions for Fortune 500 companies, this book bridges the gap between concept and implementation, exploring LangChain and Google Cloud’s enterprise-ready tools for scalable AI solutions.
You'll start by exploring the fundamentals of large language models (LLMs) and how LangChain simplifies the development of AI workflows by connecting LLMs with external data and services. This book guides you through using essential tools like the Gemini and PaLM 2 APIs, Vertex AI, and Vertex AI Search to create sophisticated, production-ready GenAI applications. You'll also overcome the context limitations of LLMs by mastering advanced techniques like Retrieval-Augmented Generation (RAG) and external memory layers.
Through practical patterns and real-world examples, you’ll gain everything you need to harness Google Cloud’s AI ecosystem, reducing the time to market while ensuring enterprise scalability. You’ll have the expertise to build robust GenAI applications that can be tailored to solve real-world business challenges.

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O autorach książki

Leonid Kuligin is an active contributor to LangChain and the author of the many Google Cloud integrations on LangChain. He has been building complex tech products for almost 20 years, developing intense data and Machine Learning applications. Leonid has a degree in Applied Mathematics and Physics, and a degree in Finance. Since 2023, he has been working with key Google Cloud customers on various generative AI initiatives.
Dr. Maximilian Tschochohei leads AI Engineering at Google Cloud Consulting EMEA and is responsible for implementing AI applications for Google Cloud customers. He brings insights into LangChain Before joining Google, he spent many years of experience in strategy and technology consulting with the Boston Consulting Group.

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