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 with Real World Projects
  name:
    name part: Ltd., Geekshub
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: moving image
  genre: videorecording
  genre: Electronic videos.
  origin info:
    place:
      place term: xx
    date issued: 2019
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 video file, approximately 29 hr., 48 min.)
  abstract: Go from Beginner to Super Advance Level in Machine Learning Algorithms using Python and Mathematical Insights About This Video Learn Machine Learning with real-world case studies Learn complex theory, algorithms and coding libraries in a very simple way In Detail Want to become a good Data Scientist? Then this is a right course for you. This course has been designed by IIT professionals who have mastered in Mathematics and Data Science. We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advance level. We have solved few Kaggle problems during this course and provided complete solutions so that students can easily compete in real world competition websites.
  note: Ltd., Geekshub.
  note: Videorecording.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web. 2019.
  note: Mode of access: World Wide Web.
  identifier: 9781838985363
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 310320
    record change date: 20260123214802.1
    record identifier: in00004254184