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. 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 LearnUse Mathematica to explore data and describe the concepts using Wolfram language commandsCreate datasets, work with data frames, and create tablesImport, export, analyze, and visualize dataWork with the Wolfram data repository Build reports on the analysisUse Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clusteringWho 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.