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Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77
Introduction to Programming with Fortran - with coverage of Fortran 90, 95, 2003 and 77
MATLAB - Modelling, Programming and Simulations
-MATLAB: Modelling, Programming and Simulations- ed. by Emilson Pereira Leite (Repost)
Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77 [Repost]
An Introduction to Programming and Numerical Methods in MATLAB [Repost]
"MATLAB: Modelling, Programming and Simulations" ed. by Emilson Pereira Leite (Repost)
Programming Social Applications: Building Viral Experiences with OpenSocial, OAuth, OpenID, and Distributed Web... (repost)
MATLAB Programming for Engineers (2nd edition) [Repost]
Sriranga Veeraraghavan, "Sams Teach Yourself Shell Programming in 24 Hours" (Repost)
Programming Computer Vision with Python - Tools and algorithms for analyzing images
Matlab: A Practical Introduction to Programming and Problem Solving (2nd edition) [Repost]
ECOOP 2011 - Object-Oriented Programming
Mobile JavaScript Application Development - Bringing Web Programming to Mobile Devices [Paperback]
Concurrent Programming on Windows (repost)
Expert WSS 3.0 and MOSS 2007 Programming (repost)
Embedded Software Design and Programming of Multiprocessor System-on-Chip (repost)
OpenCV 2 Computer Vision Application Programming Cookbook
Programming Computer Vision with Python: Tools and algorithms for analyzing images
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Programming Exploratory Data Analysis with MATLAB (Repost)
Posted on 2010-03-16
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More Exploratory Data Analysis with MATLAB By Wendy L. Martinez, Angel Martinez, Jeffrey Solka Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger and more complex data sets. There are many resources for those interested in the theory of EDA, but this is the first book to use MATLAB to illustrate the computational aspects of this discipline. Exploratory Data Analysis with MATLAB presents the methods of EDA from a computational perspective. The authors extensively use MATLAB code and algorithm descriptions to provide state-of-the-art techniques for finding patterns and structure in data. Addressing theory, they also incorporate many annotated references to direct readers to the more theoretical aspects of the methods. The book presents an approach using the basic functions from MATLAB and the MATLAB Statistics Toolbox, in order to be more accessible and enduring. It also contains pseudo-code to enable users of other software packages to implement the algorithms. This text places the tools needed to implement EDA theory at the fingertips of researchers, applied mathematicians, computer scientists, engineers, and statisticians by using a practical/computational approach.
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