Beginning mathematica and wolfram for data science : applications in data analysis, machine learning, and neural networks

Beginning mathematica and wolfram for data science applications in data analysis, machine learning, and neural networks

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....

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Bibliographic Details
Other Authors: Alva, Jalil Villalobos, author (author)
Format: eBook
Language:Inglés
Published: Berkeley, California : APress [2021]
Edition:1st ed. 2021.
Subjects:
Professional Computing.
Data Structures and Information Theory.
Artificial intelligence.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631088706719
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.

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