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

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. 

You will:

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

Jalil Villalobos Alva is a Wolfram language programmer and Mathematica user. He graduated with a degree in engineering physics from the Universidad Iberoamericana in Mexico City. His research background comprises quantum physics, bionformatics, proteomics, and protein design. His academic interests cover the topics of quantum technology, bioinformatics, machine learning, stochastic processes, and space engineering. During his idle hours he likes to play soccer, swim, and listen to music.

Front Matter
Pages i-xxiii
PDF 
Introduction to Mathematica
Jalil Villalobos Alva
Pages 1-43
Data Manipulation
Jalil Villalobos Alva
Pages 45-78
Working with Data and Datasets
Jalil Villalobos Alva
Pages 79-131
Import and Export
Jalil Villalobos Alva
Pages 133-166
Data Visualization
Jalil Villalobos Alva
Pages 167-208
Statistical Data Analysis
Jalil Villalobos Alva
Pages 209-242
Data Exploration
Jalil Villalobos Alva
Pages 243-271
Machine Learning with the Wolfram Language
Jalil Villalobos Alva
Pages 273-329
Neural Networks with the Wolfram Language
Jalil Villalobos Alva
Pages 331-373
Neural Network Framework
Jalil Villalobos Alva
Pages 375-406
Back Matter
Pages 407-416