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Essentials of Mathematical Methods in Science and Engineering
A comprehensive introduction to the multidisciplinary applications of mathematical methods, revised and updated
The second edition of Essentials of Mathematical Methods in Science and Engineering offers an introduction to the key mathematical concepts of advanced calculus, differential equations, complex... | | Applied Statistics: Theory and Problem Solutions with R
Instructs readers on how to use methods of statistics and experimental design with R software
Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds... | | |
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Building Modern Web Applications Using Angular
Key Features
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Learn about the core building blocks of Angular
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Build and architect high performance web applications
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Implement the latest JavaScript concepts in ECMAScript 2015, ECMAScript 2016, and TypeScript
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Leverage the latest Angular features to get the most out of your web
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Evolutionary Computation 1: Basic Algorithms and Operators
The original Handbook of Evolutionary Computation (Back et a1 1997) was
designed to fulfil1 the need for a broad-based reference book reflecting the
important role that evolutionary computation plays in a variety of disciplinesranging
from the natural sciences and engineering to evolutionary biology and
computer ... | | Forest Analytics with R: An Introduction (Use R!)
R is an open-source and free software environment for statistical computing
and graphics. R compiles and runs on a wide variety of UNIX platforms
(e.g., GNU/Linux and FreeBSD), Windows, and Mac OSX. Since the late
1990s, R has been developed by hundreds of contributors and new capabilities
are added each month. ... | | Introduction to Evolutionary Algorithms (Decision Engineering)
Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms.... |
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas,... | | | | Analysis of Correlated Data with SAS and R
Previously known as Statistical Methods for Health Sciences, this bestselling resource is one of the first books to discuss the methodologies used for the analysis of clustered and correlated data. While the fundamental objectives of its predecessors remain the same, Analysis of Correlated Data with SAS and R, Third Edition incorporates ... |
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