E-Books →Beginning Mathematica and Wolfram for Data Science Applications in Data Analysis, Machine Learning

You'll gain a deeper understanding of data science from a theoretical and practical perspective using Mathematica and the Wolfram Language. 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. Existing topics have been reorganized for better context and to accommodate the introduction of Notebook styles. The book also incorporates new functionalities in code versions 13 and 14 for imported and exported data.
You'll see how to use Mathematica, where data management and mathematical computations are needed. Along the way, you'll appreciate how Mathematica provides an entirely integrated platform: its symbolic and numerical calculation result in a mized syntax, 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 LearnCreate datasets, work with data frames, and create tablesImport, export, analyze, and visualize dataWork with the Wolfram data repositoryBuild 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 who are new to using Wolfram and Mathematica as a programming language or tool. Programmers should have some prior programming experience, but can be new to the Wolfram language.
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