Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll...

Familiarize yourself with Scilab using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting, and working with files in Scilab. Introduction to Scilab is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.In this book you will learn by doing, avoiding technical jargon, which makes the concepts eas...

Familiarize yourself with MATLAB using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting and working with files, numerical computation formalism, and the primary concepts of approximations. Introduction to MATLAB is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.In this book you will learn...

Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calcul...

Familiarize yourself with Octave using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting, and working with files in Octave, which can run MATLAB files without modification. Introduction to Octave is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.In this book you will learn by doing, avoidi...

Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it.Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools n...

This guide takes you straight into the attributes of Oracle Spatial and teaches you to extend, apply, and combine them with other Oracle and open source technologies. A vital manual for solving everyday problems.Key FeaturesUnderstand how to develop Oracle Spatial data models and applications that use PL/SQL and Java to solve common problems using practical, hands-on examplesDesign a data model for spatial applicationsUse standard database tech...

"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyLearning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision...

Mathematica Cookbook helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music.Although Mathematica 7 is a highly advanced computational platform, the recipes in thi...

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples...

Key FeaturesBook DescriptionThis book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.What you will learnGet to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposesCreate and manipulate an object array used by SciPyUse SciPy with large matric...

Become a proficient Octave user by learning this high-level scientific numerical tool from the ground upKey FeaturesThe easiest way to use GNU Octave's power and flexibility for data analysisWork with GNU Octave's interpreter – declare and control mathematical objects like vectors and matricesRationalize your scripts and control program flowExtend GNU Octave and implement your own functionalityGet to know the vast built-in f...