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: Learning Python for Data Science
  name:
    name part: Ustun, Ilyas
    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: 2018
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 video file, approximately 3 hr., 39 min.)
  abstract: Gain an in-depth understanding of data analysis with various Python packages About This Video Learn data analysis, manipulation, and visualization using the pandas library Create statistical plots using Matplotlib and Seaborn to help you get insights into real-size patterns hidden in data Gain an in-depth understanding of the various Python packages to perform data analysis and implement effective machine learning models In Detail Python is an open source community-supported, general-purpose programming language that, over the years, has also become one of the bastions of data science. Thanks to its flexibility and vast popularity, data analysis, visualization, and machine learning can be easily carried out with Python. This course will help you learn the tools necessary to deploy its features for data science applications. In this course, you will learn all the necessary libraries that make data analytics with Python rewarding and effective. You will get into hands-on data analysis and machine learning by coding in Python. You will also learn the NumPy library used for numerical and scientific computation. You will employ useful libraries for visualization (Matplotlib and Seaborn) to provide insights into data. Further, you will learn various steps involved in building an end-to-end machine learning solution. The ease of use and efficiency of these tools will help you learn these topics very quickly. The video course is prepared with applications in mind. You will explore coding on real-life datasets, to enable you to utilize your learning within your own projects. By the end of this course, you'll have progressed through a journey from data cleaning and preparation to creating summary tables, and from visualization to machine learning and prediction. This video course will prepare you to enter the world of data science. Welcome to our journey!
  note: Ustun, Ilyas.
  note: Videorecording.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web. 2018.
  note: Mode of access: World Wide Web.
  identifier: 9781785886928
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 300718
    record change date: 20260123213804.1
    record identifier: in00004251280