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.
