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: Python
    sub title: Data Analytics and Visualization
  name:
    name part: Vo. T. H, Phuong
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Czygan, Martin
    role:
      role term: author.
  name:
    name part: Kumar, Ashish
    role:
      role term: author.
  name:
    name part: Raman, Kirthi
    role:
      role term: author.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xx
    date issued: 2017
    edition: 1st edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (866 pages)
  abstract: Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization - predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see …
  note: Vo.T.H, Phuong.
  note: Electronic resource.
  note: Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
  note: Mode of access: World Wide Web.
  identifier: 9781788290098
  identifier: 9781788294850
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record creation date: 050417
    record change date: 20260129210750.9
    record identifier: in00004260792