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Beginning Mathematica And Wolfram For Data Science


Beginning Mathematica And Wolfram For Data Science
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Beginning Mathematica And Wolfram For Data Science


Beginning Mathematica And Wolfram For Data Science
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Author : Jalil Villalobos Alva
language : en
Publisher: Apress
Release Date : 2024-07-13

Beginning Mathematica And Wolfram For Data Science written by Jalil Villalobos Alva and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-13 with Computers categories.


Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. This second edition introduces the latest LLM Wolfram capabilities, delves into the exploration of data types in Mathematica, covers key programming concepts, and includes code performance and debugging techniques for code optimization. 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 Learn 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 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.



Beginning Mathematica And Wolfram For Data Science


Beginning Mathematica And Wolfram For Data Science
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Author : Jalil Villalobos Alva
language : en
Publisher:
Release Date : 2021

Beginning Mathematica And Wolfram For Data Science written by Jalil Villalobos Alva and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Databases categories.


Enhance your data science programming and analysis with the Wolfram programming language and Mathematica. The book will introduce you to the language and its syntax, as well as the structure of Mathematica and its advantages and disadvantages. --



Hands On Start To Wolfram Mathematica


Hands On Start To Wolfram Mathematica
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Author : Cliff Hastings
language : en
Publisher:
Release Date : 2015

Hands On Start To Wolfram Mathematica written by Cliff Hastings and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer programming categories.


For more than 25 years, Mathematica has been the principal computation environment for millions of innovators, educators, students, and others around the world. This book is an introduction to Mathematica. The goal is to provide a hands-on experience introducing the breadth of Mathematica, with a focus on ease of use. Readers get detailed instruction with examples for interactive learning and end-of-chapter exercises. Each chapter also contains authors tips from their combined 50+ years of Mathematica use.



A New Kind Of Science


A New Kind Of Science
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Author : Stephen Wolfram
language : en
Publisher: Wolfram Media
Release Date : 2018-11-30

A New Kind Of Science written by Stephen Wolfram and has been published by Wolfram Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with categories.


NOW IN PAPERBACK"€"Starting from a collection of simple computer experiments"€"illustrated in the book by striking computer graphics"€"Stephen Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe.



Programming With Mathematica


Programming With Mathematica
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Author : Paul Wellin
language : en
Publisher: Cambridge University Press
Release Date : 2013-01-10

Programming With Mathematica written by Paul Wellin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-10 with Computers categories.


This practical, example-driven introduction teaches the foundations of the Mathematica language so it can be applied to solving concrete problems.



Bayesian Logical Data Analysis For The Physical Sciences


Bayesian Logical Data Analysis For The Physical Sciences
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Author : Phil Gregory
language : en
Publisher: Cambridge University Press
Release Date : 2005-04-14

Bayesian Logical Data Analysis For The Physical Sciences written by Phil Gregory and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-14 with Mathematics categories.


Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.



An Introduction To Statistics With The Wolfram Language


An Introduction To Statistics With The Wolfram Language
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Author : Juan H. Klopper
language : en
Publisher: Wolfram Media Incorporated
Release Date : 2020-05-06

An Introduction To Statistics With The Wolfram Language written by Juan H. Klopper and has been published by Wolfram Media Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-06 with categories.




Statistics With Mathematica


Statistics With Mathematica
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Author : Martha L. Abell
language : en
Publisher: Academic Press
Release Date : 1999

Statistics With Mathematica written by Martha L. Abell and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.


Covers the use of Mathematica for applications ranging from descriptive statistics, through multiple regression and nonparametric methods; uses virtually all of Mathematica's built-in statistical commands, as well as those contained in various Mathematica packages; Additionally, the authors have written numerous procedures to extend Mathematica's capabilities, which are also included on the CD-ROM



Mathematica For Scientists And Engineers


Mathematica For Scientists And Engineers
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Author : Thomas Bazyli Bahder
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1995

Mathematica For Scientists And Engineers written by Thomas Bazyli Bahder and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.


This practical guide to Mathematica focuses on the specific needs of scientists and engineers. Problems in these fields often are non-trivial, and can push Mathematica (and any computer system) to its limits. Here the author, providing carefully chosen examples, shows how these problems can be solved.



Beginning Data Science In R


Beginning Data Science In R
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Author : Thomas Mailund
language : en
Publisher: Apress
Release Date : 2017-03-09

Beginning Data Science In R written by Thomas Mailund and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-09 with Computers categories.


Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.