Beginning Mathematica and Wolfram for data science : applications in data analysis, machine learning, and neural networks / Jalil Villalobos Alva.
2021
QA76.73.M29
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Authorized users
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Details
Title
Beginning Mathematica and Wolfram for data science : applications in data analysis, machine learning, and neural networks / Jalil Villalobos Alva.
Author
ISBN
9781484265949 (electronic bk.)
1484265947 (electronic bk.)
1484265939
9781484265932
1484265947 (electronic bk.)
1484265939
9781484265932
Published
Berkeley, CA : Apress, 2021.
Language
English
Description
1 online resource (430 pages)
Item Number
10.1007/978-1-4842-6594-9 doi
Call Number
QA76.73.M29
Dewey Decimal Classification
510.285/536
Summary
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.
Note
Includes index.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
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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.
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.