Beginning Mathematica and Wolfram for Data Science

Beginning Mathematica and Wolfram for Data Science
Author :
Publisher : Apress
Total Pages :
Release :
ISBN-10 : 1484265939
ISBN-13 : 9781484265932
Rating : 4/5 (39 Downloads)

Book Synopsis Beginning Mathematica and Wolfram for Data Science by : Jalil Villalobos Alva

Download or read book Beginning Mathematica and Wolfram for Data Science written by Jalil Villalobos Alva and published by Apress. This book was released on 2021-03-28 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book introduces 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 The fundamentals of the Wolfram Neural Network Framework and how to build your neural network for different tasks How to use pre-trained models from the Wolfram Neural Net Repository 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.


Beginning Mathematica and Wolfram for Data Science Related Books

Beginning Mathematica and Wolfram for Data Science
Language: en
Pages:
Authors: Jalil Villalobos Alva
Categories: Computers
Type: BOOK - Published: 2021-03-28 - Publisher: Apress

DOWNLOAD EBOOK

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book introduc
Hands-on Start to Wolfram Mathematica
Language: en
Pages: 0
Authors: Cliff Hastings
Categories: Computers
Type: BOOK - Published: 2016 - Publisher:

DOWNLOAD EBOOK

For more than 25 years, Mathematica has been the principal computation environment for millions of innovators, educators, students, and others around the world.
Introduction to Machine Learning
Language: en
Pages: 189
Authors: Shan-e-Fatima
Categories: Education
Type: BOOK - Published: 2023-09-25 - Publisher: Blue Rose Publishers

DOWNLOAD EBOOK

With the use of machine learning (ML), which is a form of artificial intelligence (AI), software programmers may predict outcomes more accurately without having
Mathematica Data Analysis
Language: en
Pages: 164
Authors: Sergiy Suchok
Categories: Computers
Type: BOOK - Published: 2015-12-24 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Learn and explore the fundamentals of data analysis with power of Mathematica About This Book Use the power of Mathematica to analyze data in your applications
A New Kind of Science
Language: en
Pages: 1197
Authors: Stephen Wolfram
Categories: Cellular automata
Type: BOOK - Published: 2002 - Publisher:

DOWNLOAD EBOOK

This work presents a series of dramatic discoveries never before made public. Starting from a collection of simple computer experiments---illustrated in the boo