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Modeling with Data - Tools and Techniques for Scientific Computing

simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply;

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Introduction to Computational Modeling Using C and Open-Source Tools

include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing;

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Introduction to Computational Modeling Using C and Open-Source Tools

include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing;

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Reliability and Risk Modeling of Engineering Systems

of industrial and manufacturing systems, along with other complex engineering equipment. Computing techniques like data analytics, failure mode and;

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Introduction to Computational Models with Python

techniques for designing and implementing problem solutions, independent of software and hardware tools Programming principles with the Python;

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Introduction to Computational Models with Python

and techniques for designing and implementing problem solutions, independent of software and hardware tools Programming principles with;

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Mastering Python Scientific Computing

A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book * The basics;

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Perception-based Data Mining and Decision Making in Economics and Finance

information and knowledge usually extracted from the analysis of large amounts of data. Data mining techniques enabled with the capability to;

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Applied Modeling Techniques and Data Analysis 1 - Computational Data Analysis Methods and Tools

on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a;

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Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology

. . Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with;

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Data Driven Modeling & Scientific Comput

Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Applied Modeling Techniques and Data Analysis 2 - Financial, Demographic, Stochastic and Statistical Models and Methods

on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 2 is a;

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Beginning MATLAB and Simulink

started using MATLAB and Simulink Carry out data visualization with MATLAB Gain the programming and modeling essentials of MATLAB Build a GUI;

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IPython Interactive Computing and Visualization Cookbook

interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling;

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Scientific Computing

Computational Science and Applications Scientific Computing + Data Management + Cryptography Novel Scientific And Engineering Algorithms and;

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A Framework for Model-Driven Scientific Workflow Engineering

Scientific workflows are one important means in the context of data-intensive science for reliable and efficient scientific data processing;

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Systems Simulation and Modeling for Cloud Computing and Big Data Applications

Systems Simulation and Modelling for Cloud Computing and Big Data Applications provides readers with the most current approaches to;

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Graphics and Visualization

This book is a comprehensive introduction to visual computing, dealing with the modeling and synthesis of visual data by means of computers;

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Computational Immunology

techniques to study immunological processes at a systems level, along with the concept of multi-scale modeling. The book's emphasis is on;

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Multicore Software Engineering, Performance, and Tools

. The accepted papers are organized into three main sessions and cover topics such as software engineering for multicore systems;

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Mastering Spark with R The Complete Guide to LargeScale Analysis and Modeling

of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large;

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Practical Computing For Biologists

larger data sets and analyses without suitable tools to deal with them. Many biologists end up using spreadsheet programs for most of their data;

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Applied Parallel and Scientific Computing

interval methods, real-time access and processing of large data sets, linear algebra algorithms and software for multicore and hybrid architectures;

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Hydroinformatics

hydrological data available today. Linking hydrological science with computer engineering, networking, and database science, this book lays a;

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Hydroinformatics

hydrological data available today. Linking hydrological science with computer engineering, networking, and database science, this book lays a;

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