Beginning Mathematica and Wolfram for Data Science
Beginning Mathematica and Wolfram for Data Science

Author: Jalil Villalobos Alva

Publisher: Apress

Published: 2021-03-28

Total Pages:

ISBN-13: 9781484265932

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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.

Hands-on Start to Wolfram Mathematica
Hands-on Start to Wolfram Mathematica

Author: Cliff Hastings

Publisher:

Published: 2016

Total Pages: 0

ISBN-13: 9781579550127

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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.

Mathematica Data Analysis
Mathematica Data Analysis

Author: Sergiy Suchok

Publisher: Packt Publishing Ltd

Published: 2015-12-24

Total Pages: 164

ISBN-13: 178588445X

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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 Discover the capabilities of data classification and pattern recognition offered by Mathematica Use hundreds of algorithms for time series analysis to predict the future Who This Book Is For The book is for those who want to learn to use the power of Mathematica to analyze and process data. Perhaps you are already familiar with data analysis but have never used Mathematica, or you know Mathematica but you are new to data analysis. With the help of this book, you will be able to quickly catch up on the key points for a successful start. What You Will Learn Import data from different sources to Mathematica Link external libraries with programs written in Mathematica Classify data and partition them into clusters Recognize faces, objects, text, and barcodes Use Mathematica functions for time series analysis Use algorithms for statistical data processing Predict the result based on the observations In Detail There are many algorithms for data analysis and it's not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel. Style and approach This book takes a step-by-step approach, accompanied by examples, so you get a better understanding of the logic of writing algorithms for data analysis in Mathematica. We provide a detailed explanation of all the nuances of the Mathematica language, no matter what your level of experience is.

Introduction to Machine Learning
Introduction to Machine Learning

Author: Shan-e-Fatima

Publisher: Blue Rose Publishers

Published: 2023-09-25

Total Pages: 189

ISBN-13:

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With the use of machine learning (ML), which is a form of artificial intelligence (AI), software programmers may predict outcomes more accurately without having to be explicitly instructed to do so. In order to forecast new output values, machine learning algorithms use historical data as input. Machine learning is frequently used in recommendation engines. Business process automation (BPA), predictive maintenance, spam filtering, malware threat detection, and fraud detection are a few additional common uses. Machine learning is significant because it aids in the development of new goods and provides businesses with a picture of trends in consumer behavior and operational business patterns. For many businesses, machine learning has emerged as a key competitive differentiation. The fundamental methods of machine learning are covered in the current book.

A New Kind of Science
A New Kind of Science

Author: Stephen Wolfram

Publisher:

Published: 2002

Total Pages: 1197

ISBN-13: 9780713991161

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This work presents a series of dramatic discoveries never before made public. Starting from a collection of simple computer experiments---illustrated in the book by striking computer graphics---Wolfram shows how their unexpected results force a whole new way of looking at the operation of our universe. Wolfram uses his approach to tackle a remarkable array of fundamental problems in science: from the origin of the Second Law of thermodynamics, to the development of complexity in biology, the computational limitations of mathematics, the possibility of a truly fundamental theory of physics, and the interplay between free will and determinism.

Programming with Mathematica®
Programming with Mathematica®

Author: Paul Wellin

Publisher: Cambridge University Press

Published: 2013-01-10

Total Pages: 731

ISBN-13: 1107009464

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

An Elementary Introduction to the Wolfram Language
An Elementary Introduction to the Wolfram Language

Author: Stephen Wolfram

Publisher: Wolfram Research, Incorporated

Published: 2017

Total Pages: 0

ISBN-13: 9781944183059

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The Wolfram Language represents a major advance in programming languages that makes leading-edge computation accessible to everyone. Unique in its approach of building in vast knowledge and automation, the Wolfram Language scales from a single line of easy-to-understand interactive code to million-line production systems. This book provides an elementary introduction to the Wolfram Language and modern computational thinking. It assumes no prior knowledge of programming, and is suitable for both technical and non-technical college and high-school students, as well as anyone with an interest in the latest technology and its practical application.

Think Julia
Think Julia

Author: Ben Lauwens

Publisher: "O'Reilly Media, Inc."

Published: 2019-04-05

Total Pages: 298

ISBN-13: 1492044989

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If you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand types, methods, and multiple dispatch Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design and data structures through case studies

Mathematica Reference Guide
Mathematica Reference Guide

Author: Stephen Wolfram

Publisher: Addison Wesley

Published: 1992

Total Pages: 330

ISBN-13:

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This authoritative reference guide for Mathematica, Version 2 is designed for convenient reference while users work with the Mathematica program. Mathematicians, scientists, engineers, and programmers using Mathematica will find the reference easy to handle, easy to carry, and packed with essential information.