Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs 1st Edition 276180

Паперова книга
276180
Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs 1st Edition - фото 1
27.05
3'200

Все про “Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs 1st Edition”

Від видавця

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation.
With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI.
Learn how to empower AI to work for you. This book explains:
  • The structure of the interaction chain of your program's AI model and the fine-grained steps in between
  • How AI model requests arise from transforming the application problem into a document completion problem in the model training domain
  • The influence of LLM and diffusion model architecture—and how to best interact with it
  • How these principles apply in practice in the domains of natural language processing, text and image generation, and code
About the Author
James Phoenix has a background in building reliable data pipelines for marketing teams, including automation of thousands of recurring marketing tasks. He has taught 40+ Data Science bootcamps for General Assembly.
Mike Taylor built and ran a 50-person marketing agency, including working on innovation projects with Unilever, Nestle, and Facebook. Over 300,000 people have taken his marketing courses on LinkedIn Learning.

Рецензії

0

Всі характеристики

Товар входить до категорії

  • Самовивіз з відділень поштових операторів від 45 ₴ - 80 ₴
  • Доставка поштовими сервісами - тарифи перевізника
Схожі товари
Applied Deep Learning with TensorFlow 2. 2nd Ed.
244660
Umberto Michelucci
2'100 ₴
Introducing MLOps. How to Scale Machine Learning in the Enterprise. 1st Ed.
244757
Mark Treveil, Nicolas Omont, Cl?ment Stenac
2'100 ₴
AI and Machine Learning for On-Device Development: A Programmer's Guide. 1st Ed.
244740
Laurence Moroney
2'200 ₴
Practical AI on the Google Cloud Platform. Learn How to Use the Latest AI Cloud Services on the Google Cloud Platform
173878
Micheal Lanham
2'600 ₴
Practical Weak Supervision: Doing More with Less Data. 1st Ed.
244781
Wee Hyong Tok, Amit Bahree
2'600 ₴
Штучний інтелект: сучасний підхід (AIMA-2). 2-е вид.
891
Стюарт РасселПитер Норвиг
2'700 ₴
Machine Learning System Design Interview
239864
Ali AminianAlex Xu
2'700 ₴
Computer Vision: Object Detection In Adversarial Vision 1st Edition
269108
Mrinal Kanti Bhowmik
2'700 ₴