rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Optimizing prompt engineering for generative AI
  name:
    name part: Herman, Erik
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Knovel (Firm)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: mau
    date issued: 2025
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: "As artificial intelligence continues to permeate various facets of our lives, from customer service to healthcare and beyond, the ability to effectively communicate with these systems becomes increasingly critical. The art and science of prompt engineering, the practice of designing and refining the inputs that guide AI responses, is at the heart of this interaction. This book, "Prompt Engineering for Generative AI: Optimizing Conversational AI," seeks to provide a comprehensive guide to mastering this essential skill"--
  table of contents: Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Prompt Engineering -- Chapter 2: Crafting Effective Prompts -- Chapter 3: Prompts and Contextual Understanding -- Chapter 4: Fine-Tuning Prompts for Specific Use Cases -- Chapter 5: Monitoring and Evaluating Prompt Performance -- Chapter 6: Advanced Prompt Engineering Techniques -- Chapter 7: Hands-On Exercises and Case Studies -- Chapter 8: Best Practices and Future Directions -- Index
  note: Erik Herman.
  note: Includes index.
  subject:
    topic: Artificial intelligence
  subject:
    topic: Electronic data processing
    topic: Data entry
  subject:
    topic: Intelligence artificielle
  subject:
    topic: Saisie des données (Informatique)
  subject:
    topic: artificial intelligence
  subject:
    topic: COMPUTERS / Intelligence (AI) & Semantics
  classification: Q335 .H47 2025
  classification: 006.3
  related item:
    title info:
      title: MLI generative AI series
  related item:
    title info:
      title: Optimizing Prompt Engineering for Generative AI
    name:
      name part: HERMAN, Erik
    origin info:
      publisher: Herndon, VA : Mercury Learning & Information,c2025
  identifier: 1501521357
  identifier: 9781501521355
  identifier: 1501521373
  identifier: 9781501521379
  identifier: 9781501523694
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 240810
    record change date: 20260121211151.2
    record identifier: in00005676612
    language of cataloging:
      language term: eng