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: Machine Learning: Hands - On for Developers and Technical Professionals
  name:
    name part: Bell, Jason
    role:
      role term: creator
  type of resource: text
  origin info:
    place:
      place term: vn
    place:
      place term: Indianapolis
    publisher: John Wiley & Sons
    date issued: 2015
    date issued: yyyy
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: 408tr. ; 23.5cm
  abstract: Dig deep into the data with a hands-on guide to machine learning. Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data.
  note: Jason Bell
  note: Tặng
  subject:
    topic: Machine Learning
  subject:
    topic: Big Data
  subject:
    topic: Computer Science
  classification: 006.3 M102-I
  identifier: 9781118889060
  record info:
    record creation date: 220225
    record change date: 20220325152800.000
    record identifier: TVCDKTCT127453