An Introduction to Statistics with the Wolfram Language
Author: Juan H. Klopper
Publisher: Wolfram Media Incorporated
Published: 2020-05-06
Total Pages:
ISBN-13: 9781579550332
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Hands-on Start to Wolfram Mathematica
Author: Cliff Hastings
Publisher:
Published: 2016
Total Pages: 0
ISBN-13: 9781579550127
DOWNLOAD EBOOKFor 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.
Introduction to Machine Learning
Author: Shan-e-Fatima
Publisher: Blue Rose Publishers
Published: 2023-09-25
Total Pages: 189
ISBN-13:
DOWNLOAD EBOOKWith 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.
Mathematical Statistics with Mathematica
Author: Colin Rose
Publisher: Springer
Published: 2002
Total Pages: 508
ISBN-13: 9780387952345
DOWNLOAD EBOOKThis text and software package presents a unified approach for doing mathematical statistics with Mathematica. The mathStatica software empowers the student with the ability to solve difficult problems. The professional statistician should be able to tackle tricky multivariate distributions, generating functions, inversion theorems, symbolic maximum likelihood estimation, unbiased estimation, and the checking and correcting of textbook formulae. This is the ideal companion for researchers and students in statistics, econometrics, engineering, physics, psychometrics, economics, finance, biometrics, and the social sciences. The mathStatica CD-ROM includes: mathStatica - the applications pack for mathematical statistics, custom Mathematica palettes, live interactive book that is identical to the printed text, online help, and a trial version of Mathematica 4.0.
Introduction to Mathematica® for Physicists
Author: Andrey Grozin
Publisher: Springer Science & Business Media
Published: 2013-08-26
Total Pages: 215
ISBN-13: 3319008943
DOWNLOAD EBOOKThe basics of computer algebra and the language of Mathematica are described in this textbook, leading towards an understanding of Mathematica that allows the reader to solve problems in physics, mathematics, and chemistry. Mathematica is the most widely used system for doing mathematical calculations by computer, including symbolic and numeric calculations and graphics. It is used in physics and other branches of science, in mathematics, education and many other areas.
Beginning Mathematica and Wolfram for Data Science
Author: Jalil Villalobos Alva
Publisher: Apress
Published: 2021-03-28
Total Pages:
ISBN-13: 9781484265932
DOWNLOAD EBOOKEnhance 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.
The Student's Introduction to Mathematica and the Wolfram Language
Author: Bruce F. Torrence
Publisher: Cambridge University Press
Published: 2019-05-16
Total Pages: 550
ISBN-13: 110831404X
DOWNLOAD EBOOKThe unique feature of this compact student's introduction to Mathematica® and the Wolfram LanguageTM is that the order of the material closely follows a standard mathematics curriculum. As a result, it provides a brief introduction to those aspects of the Mathematica® software program most useful to students. Used as a supplementary text, it will help bridge the gap between Mathematica® and the mathematics in the course, and will serve as an excellent tutorial for former students. There have been significant changes to Mathematica® since the second edition, and all chapters have now been updated to account for new features in the software, including natural language queries and the vast stores of real-world data that are now integrated through the cloud. This third edition also includes many new exercises and a chapter on 3D printing that showcases the new computational geometry capabilities that will equip readers to print in 3D.
Introduction to Number Theory
Author: Anthony Vazzana
Publisher: CRC Press
Published: 2007-10-30
Total Pages: 530
ISBN-13: 1584889381
DOWNLOAD EBOOKOne of the oldest branches of mathematics, number theory is a vast field devoted to studying the properties of whole numbers. Offering a flexible format for a one- or two-semester course, Introduction to Number Theory uses worked examples, numerous exercises, and two popular software packages to describe a diverse array of number theory topi
Mathematica Reference Guide
Author: Stephen Wolfram
Publisher: Addison Wesley Publishing Company
Published: 1992
Total Pages: 330
ISBN-13:
DOWNLOAD EBOOKThis 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.
A New Kind of Science
Author: Stephen Wolfram
Publisher:
Published: 2002
Total Pages: 1197
ISBN-13: 9780713991161
DOWNLOAD EBOOKThis 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.
