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: Beginning Mathematica and Wolfram for data science
    sub title: applications in data analysis, machine learning, and neural networks
  name:
    name part: Villalobos Alva, Jalil.
    role:
      role term: creator
  type of resource: text
  genre: elektronické knihy
  genre: electronic books
  origin info:
    place:
      place term: cau
    date issued: 2021
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (430 pages)
  abstract: Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book will introduce you to the Wolfram programming language and its syntax, as well as the structure of Mathematica and its advantages and disadvantages. You'll see how to use the Wolfram language for data science from a theoretical and practical perspective. Learning this language makes your data science code better because it is very intuitive and comes with pre-existing functions that can provide a welcoming experience for those who use other programming languages. You'll cover how to use Mathematica where data management and mathematical computations are needed. Along the way you'll appreciate how Mathematica provides a complete integrated platform: it has a mixed syntax as a result of its symbolic and numerical calculations allowing it to carry out various processes without superfluous lines of code. You'll learn to use its notebooks as a standard format, which also serves to create detailed reports of the processes carried out. What You Will Learn Use Mathematica to explore data and describe the concepts using Wolfram language commands Create datasets, work with data frames, and create tables Import, export, analyze, and visualize data Work with the Wolfram data repository Build reports on the analysis Use Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clustering Who This Book Is For Data scientists new to using Wolfram and Mathematica as a language/tool to program in. Programmers should have some prior programming experience, but can be new to the Wolfram language.
  table of contents: 1. Introduction to Mathematica -- 2. Data Manipulation -- 3. Working with Data and Datasets -- 4. Import and Export -- 5. Data Visualization -- 6. Statistical Data Analysis -- 7. Data Exploration -- 8. Machine Learning with the Wolfram Language -- 9. Neural Networks with the Wolfram Language -- 10. Neural Network Framework.
  note: Jalil Villalobos Alva.
  note: Includes index.
  note: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty
  subject:
    topic: Mathematica (Computer program language)
  subject:
    topic: Wolfram language (Computer program language)
  subject:
    topic: Mathematics
    topic: Data processing
  subject:
    topic: Artificial intelligence
  related item:
    title info:
      title: Beginning Mathematica and Wolfram for Data Science
    name:
      name part: Villalobos Alva, Jalil.
    origin info:
      publisher: Berkeley, CA : Apress L.P., ©2021
  identifier: 9781484265949
  identifier: 1484265947
  identifier: 1484265939
  identifier: 9781484265932
  identifier: https://proxy.k.utb.cz/login
  access condition: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty
  record info:
    record content source: EBLCP
    record creation date: 210206
    record change date: 20240717213016.0
    record identifier: kn-on1236267897
    language of cataloging:
      language term: eng