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    Generative AI on Google Cloud with LangChain: Design scalable generative AI solutions with Python, LangChain, and Vertex AI

    Posted By: naag
    Generative AI on Google Cloud with LangChain: Design scalable generative AI solutions with Python, LangChain, and Vertex AI

    Generative AI on Google Cloud with LangChain: Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud
    English | 2024 | ASIN: B0DKT8DCRT | 306 pages | EPUB (True) | 9.79 MB

    Turn challenges into opportunities by learning advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools

    Key Features
    Solve real-world business problems with hands-on examples of GenAI applications on Google Cloud
    Learn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethics
    Build and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AI
    Purchase of the print or Kindle book includes a free PDF eBook
    Book Description
    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.

    What you will learn
    Build enterprise-ready applications with LangChain and Google Cloud
    Navigate and select the right Google Cloud generative AI tools
    Apply modern design patterns for generative AI applications
    Plan and execute proof-of-concepts for enterprise AI solutions
    Gain hands-on experience with LangChain's and Google Cloud's AI products
    Implement advanced techniques for text generation and summarization
    Leverage Vertex AI Search and other tools for scalable AI solutions
    Who this book is for
    If you’re an application developer or ML engineer eager to dive into GenAI, this book is for you. Whether you're new to LangChain or Google Cloud, you'll learn how to use these tools to build scalable AI solutions. This book is ideal for developers familiar with Python and machine learning basics looking to apply their skills in GenAI. Professionals who want to explore Google Cloud's powerful suite of enterprise-grade GenAI products and their implementation will also find this book useful.

    Table of Contents
    Using LangChain with Google Cloud
    Foundational Models on Google Cloud
    Grounding Responses on Google Cloud
    Vector Search on Google Cloud
    Advanced Techniques for Parsing and Ingesting Documents
    Multimodality
    Working with Long Context
    Building Chatbots
    Tools and Function Calling
    Agents in Generative AI
    Agentic Workflows
    Evaluating GenAI Applications
    GenAI System Design
    Appendix 1 - Overview of Generative AI
    Appendix 2 - Google Cloud Foundations