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: Intelligent Techniques for Data Science
  name:
    name part: Akerkar, Rajendra.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Sajja, Priti Srinivas.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 272 p. 121 illus., 57 illus. in color. online resource.
  abstract: This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions. The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
  table of contents: Preface -- Introduction -- Data Analytics -- Basic Learning Algorithms -- Fuzzy Logic -- Artificial Neural Networks -- Genetic Algorithms and Evolutionary Computing -- Other Metaheuristics and Classification Approaches -- Analytics and Big Data -- Data Analytics Using R -- Appendix I: Tools for Data Science -- Appendix II: Tools for Computational Intelligence.
  note: by Rajendra Akerkar, Priti Srinivas Sajja.
  subject:
    topic: Computer science
  subject:
    topic: Knowledge management
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Knowledge Management
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319292069
  identifier: http://dx.doi.org/10.1007/978-3-319-29206-9
  record info:
    record creation date: 161011
    record change date: 20161011124425.0
    record identifier: 978-3-319-29206-9