Beginning Mathematica and Wolfram for Data Science (PDF)

Name: Beginning Mathematica and Wolfram for Data Science
Brand: APress
SKU: 139122609
Price: 58.59 EUR
Availability: OnlineOnly

Applications in Data Analysis, Machine Learning, and Neural Networks (Sprache: Englisch)

Autor: Jalil Villalobos Alva

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Beginning Mathematica and Wolfram for Data Science, Jalil Villalobos Alva

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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...

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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.

You will:

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

Autoren-Porträt von Jalil Villalobos Alva

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.