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Prompt Engineering for LLMs The Art and Science of Building Large Language Model-Based Applications - John Berryman, Albert Ziegler 2025 /RETAIL PDF | /RETAIL EPUB O’Reilly Media, Inc. BOOKS
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Prompt Engineering for LLMs The Art and Science of Building Large Language Model-Based Applications
Author: John Berryman, Albert Ziegler
Year: 2025
Pages: 282
Format: /RETAIL PDF | /RETAIL EPUB
File size: 22.5 MB
Language: ENG



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Prompt Engineering for LLMs The Art and Science of Building Large Language ModelBased Applications Introduction The world we live in today is vastly different from the one our parents or grandparents grew up in. With the advent of the internet, social media, and other digital technologies, information is more accessible than ever before. However, this abundance of information has also led to an explosion of misinformation, disinformation, and outright lies. This has made it increasingly difficult for individuals to discern fact from fiction, leading to a breakdown in trust and communication among people. In response, researchers have turned to natural language processing (NLP) and machine learning (ML) to develop large language models (LLMs) that can help us better understand and communicate with each other. In his groundbreaking book, "Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications author John Berryman, Albert Ziegler explores the concept of prompt engineering as a solution to the challenges posed by the proliferation of misinformation. By using LLMs to generate coherent and contextually appropriate text, prompt engineering offers a way to automate the process of creating high-quality content that is both informative and engaging.
Оперативное проектирование для LLM Искусство и наука создания приложений на основе моделей на больших языках Введение Мир, в котором мы живем сегодня, значительно отличается от того, в котором выросли наши родители или бабушки и дедушки. С появлением интернета, социальных сетей и других цифровых технологий информация стала более доступной, чем когда-либо прежде. Однако это обилие информации также привело к взрыву дезинформации, дезинформации и откровенной лжи. Из - за этого людям все труднее отличить факты от вымысла, что приводит к разрушению доверия и коммуникации между людьми. В ответ исследователи обратились к обработке естественного языка (NLP) и машинному обучению (ML) для разработки больших языковых моделей (LLM), которые могут помочь нам лучше понимать и общаться друг с другом. В своей новаторской книге «Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications» автор Джон Берриман, Альберт Зиглер исследует концепцию быстрого инжиниринга как решение проблем, связанных с распространением дезинформации. Используя LLM для создания согласованного и соответствующего контексту текста, оперативная инженерия предлагает способ автоматизации процесса создания высококачественного контента, который является как информативным, так и увлекательным.
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