Beginning Mathematica and Wolfram for Data Science

Applications in Data Analysis, Machine Learning, and Neural Networks

Authors: Villalobos Alva, Jalil

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  • The first introduction to data science using Mathematica and Wolfram 
  • Covers very popular in-demand topics such as machine learning and neural networks
  • Includes freely available source code
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eBook $34.99
price for USA
  • ISBN 978-1-4842-6594-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
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  • Immediate eBook download after purchase
Softcover $44.99
price for USA
  • ISBN 978-1-4842-6593-2
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

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.

About the authors

Jalil Villalobos Alva is a Wolfram language programmer and Mathematica user. He graduated with a degree in engineering physics from the Universidad Iberoamericana in Mexico City. His research background comprises quantum physics, bionformatics, proteomics, and protein design. His academic interests cover the topics of quantum technology, bioinformatics, machine learning, stochastic processes, and space engineering. During his idle hours he likes to play soccer, swim, and listen to music.

Table of contents (10 chapters)

Table of contents (10 chapters)

Buy this book

eBook $34.99
price for USA
  • ISBN 978-1-4842-6594-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $44.99
price for USA
  • ISBN 978-1-4842-6593-2
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock

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Bibliographic Information

Bibliographic Information
Book Title
Beginning Mathematica and Wolfram for Data Science
Book Subtitle
Applications in Data Analysis, Machine Learning, and Neural Networks
Authors
Copyright
2021
Publisher
Apress
Copyright Holder
Jalil Villalobos Alva
eBook ISBN
978-1-4842-6594-9
DOI
10.1007/978-1-4842-6594-9
Softcover ISBN
978-1-4842-6593-2
Edition Number
1
Number of Pages
XXIII, 416
Number of Illustrations
290 b/w illustrations, 54 illustrations in colour
Topics