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Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks...
Modelling Metabolism with Mathematica
Modelling Metabolism with Mathematica
With the advent of sophisticated general programming environments like Mathematica, the task of developing new models of metabolism and visualizing their responses has become accessible to students of biochemistry and the life sciences in general. Modelling Metabolism with Mathematica presents the approaches, methods, tools, and algorithms...
Exploring Abstract Algebra With Mathematica®
Exploring Abstract Algebra With Mathematica®
This upper-division laboratory supplement for courses in abstract algebra consists of several Mathematica packages programmed as a foundation for group and ring theory. Additionally, the "user's guide" illustrates the functionality of the underlying code, while the lab portion of the book reflects the contents of the...
Game Theory: An Introduction
Game Theory: An Introduction

An exciting new edition of the popular introduction to game theory and its applications

The thoroughly expanded Second Edition presents a unique, hands-on approach to game theory. While most books on the subject are too abstract or too basic for mathematicians, Game Theory: An Introduction, Second...

The Art of Modeling in Science and Engineering with Mathematica
The Art of Modeling in Science and Engineering with Mathematica
Modeling is practiced in engineering and all physical sciences. Many specialized texts exist - written at a high level - that cover this subject. However, students and even professionals often experience difficulties in setting up and solving even the simplest of models. This can be attributed to three difficulties: the proper choice of model,...
Maple and Mathematica: A Problem Solving Approach for Mathematics
Maple and Mathematica: A Problem Solving Approach for Mathematics
In the history of mathematics there are many situations in which calculations were performed incorrectly for important practical applications. Let us look at some examples, the history of computing the number π began in Egypt and Babylon about 2000 years BC, since then many mathematicians have calculated π (e.g.,...
Algorithmic Algebra (Monographs in Computer Science)
Algorithmic Algebra (Monographs in Computer Science)
Algorithmic Algebra studies some of the main algorithmic tools of computer algebra, covering such topics as Gröbner bases, characteristic sets, resultants and semialgebraic sets. The main purpose of the book is to acquaint advanced undergraduate and graduate students in computer science, engineering and mathematics with the...
Mathematica® in Action: Problem Solving Through Visualization and Computation
Mathematica® in Action: Problem Solving Through Visualization and Computation

In this third edition of Mathematica in Action, award-winning author Stan Wagon guides beginner and veteran users alike through Mathematica's powerful tools for mathematical exploration.  The transition to Mathematica 7 is made smooth with plenty of examples and case studies that utilize Mathematica's newest tools, such as...

Advanced Engineering Mathematics
Advanced Engineering Mathematics

Advanced Engineering Mathematics provides comprehensive and contemporary coverage of key mathematical ideas, techniques, and their widespread applications, for students majoring in engineering, computer science, mathematics and physics. Using a wide range of examples throughout the book, Jeffrey illustrates how to construct simple...

Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica® Support
Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica® Support
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...
Mathematica by Example
Mathematica by Example
Mathematica bv Example is intended to bridge the gap which has existed between the very elementary handbooks available on Mathematica and those reference books written for the more advanced Mathematica users. This book is an extension of a manuscript which was developed to quickly introduce enough Mathematica commands to a group of...
Exploring Scanning Probe Microscopy with MATHEMATICA
Exploring Scanning Probe Microscopy with MATHEMATICA
This second edition of the book Exploring Scanning Probe Microscopy with Mathematica is a revised and extended version of the first edition. It consists of a collection of self-contained, interactive, computational examples from the fields of scanning tunneling microscopy, scanning force microscopy, and related technologies, using Mathematica...
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