Beginning Mathematica and Wolfram for Data Science: Applications in Data Analysis, Machine Learning, and Neural Networks

© Jalil Villalobos Alva 2021

J. Villalobos AlvaBeginning Mathematica and Wolfram for Data Sciencehttps://doi.org/10.1007/978-1-4842-6594-9_1

1. Introduction to Mathematica

Jalil Villalobos Alva¹  

(1)

Mexico City, Mexico

 

The chapter begins with a preliminary introduction to why Mathematica is a useful and practical tool. So, core concepts of the Wolfram Language as well as its syntax will be examined and revised. The chapter will explain the internal structure of Mathematica, how it is designed, and how to insert code. The concept of a notebook will be introduced, which is important to understand the type of format that Mathematica handles. At this point we will see how a notebook can include code and text at the same time, considering that a notebook ...