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
By 作者:Jalil Villalobos Alva
Publisher Finelybook 出版社 : Apress; 1st ed. edition (February 2, 2021)
Language : English
pages 页数: 440 pages
ISBN-13 : 9781484265932
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

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