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: How to build good AI solutions when data is scarce
    sub title: data-efficient AI techniques are emerging, and that means you don't always need large volumes of labeled data to train AI systems based on neural networks
  name:
    name part: Ramakrishnan, Rama
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: mau
    date issued: 2022
    edition: [First edition].
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (11 pages) : illustrations
  abstract: Developing AI systems based on neural networks can require large volumes of labeled training data, which can be hard to obtain in some settings. New techniques for reducing the number of labeled examples needed to build accurate models are now emerging to address this problem. These approaches encompass ways to transfer models across related problems and to pretrain models with unlabeled data. They also include emerging best practices around data-centric artificial intelligence.
  note: Rama Ramakrishnan.
  note: "Reprint 64202."
  note: Includes bibliographical references.
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Business intelligence
    topic: Data processing
  subject:
    topic: Management
    topic: Data processing
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Management
    topic: Data processing
  classification: TA347.A78
  classification: 006.3
  identifier: 53863MIT64202 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 221213
    record change date: 20260128222555.3
    record identifier: in00004673324
    language of cataloging:
      language term: eng