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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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Villalobos Alva, Jalil
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berkeley, CA : Apress, 2021.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Beginning Mathematica and Wolfram for data science :  |b applications in data analysis, machine learning, and neural networks /  |c Jalil Villalobos Alva. 
264 1 |a Berkeley, CA :  |b Apress,  |c 2021. 
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520 |a 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. 
505 0 |a 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. 
500 |a Includes index. 
590 |a Knovel  |b ACADEMIC - Software Engineering 
590 |a Knovel  |b ACADEMIC - General Engineering & Project Administration 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Mathematica (Computer program language) 
650 0 |a Wolfram language (Computer program language) 
650 0 |a Mathematics  |x Data processing. 
650 6 |a Mathematica (Langage de programmation) 
650 6 |a Wolfram (Langage de programmation) 
650 6 |a Mathématiques  |x Informatique. 
650 7 |a Mathematica (Computer program language)  |2 fast 
650 7 |a Mathematics  |x Data processing  |2 fast 
650 7 |a Wolfram language (Computer program language)  |2 fast 
776 0 8 |i Print version:  |a Villalobos Alva, Jalil.  |t Beginning Mathematica and Wolfram for Data Science.  |d Berkeley, CA : Apress L.P., ©2021  |z 9781484265932 
856 4 0 |u https://appknovel.uam.elogim.com/kn/resources/kpBMWDSAD1/toc  |z Texto completo 
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938 |a ProQuest Ebook Central  |b EBLB  |n EBL6467886 
938 |a EBSCOhost  |b EBSC  |n 2740391 
938 |a YBP Library Services  |b YANK  |n 301912884 
994 |a 92  |b IZTAP