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: Applied machine learning and AI for engineers
    sub title: solve business problems that can't be solved algorithmically
  name:
    name part: Prosise, Jeff
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  origin info:
    place:
      place term: mau
    date issued: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : color illustrations
  abstract: While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company. Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equations--just a fast start for engineers and software developers, complete with hands-on examples. This book helps you: Learn what machine learning and deep learning are and what they can accomplish Understand how popular learning algorithms work and when to apply them Build machine learning models in Python with Scikit-Learn, and neural networks with Keras and TensorFlow Train and score regression models and binary and multiclass classification models Build facial recognition models and object detection models Build language models that respond to natural-language queries and translate text to other languages Use Cognitive Services to infuse AI into the apps that you write.
  note: Jeff Prosise.
  note: Includes index.
  subject:
    topic: Machine learning
  subject:
    topic: Artificial intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Machine learning
  classification: Q325.5 .P76 2023
  classification: 006.31
  related item:
    identifier: (OCoLC)1322366332
  identifier: 9781492098027
  identifier: 1492098027
  identifier: 1492098051
  identifier: 9781492098058
  identifier: 9781492098041 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 221114
    record change date: 20260128224801.2
    record identifier: in00004672953
    language of cataloging:
      language term: eng