Description

Book Synopsis

Learn to build cost-effective apps using Large Language Models

In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you''ll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning.

The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You''ll also find:

  • Effective strategies to address the challenge of the high computational cost associated with LLMs
  • Assist

Large Language ModelBased Solutions

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Order before 4pm today for delivery by Fri 19 Dec 2025.

A Paperback by S Subramanian

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    View other formats and editions of Large Language ModelBased Solutions by S Subramanian

    Publisher: John Wiley & Sons
    Publication Date: 4/29/2024
    ISBN13: 9781394240722, 978-1394240722
    ISBN10: 1394240724

    Description

    Book Synopsis

    Learn to build cost-effective apps using Large Language Models

    In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you''ll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning.

    The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You''ll also find:

    • Effective strategies to address the challenge of the high computational cost associated with LLMs
    • Assist

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