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Essentials of Mathematical Methods in Science and Engineering
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
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...

Algorithms and Programming: Problems and Solutions (Springer Undergraduate Texts in Mathematics and Technology)
Algorithms and Programming: Problems and Solutions (Springer Undergraduate Texts in Mathematics and Technology)
Somebody once said that one may prove the correctness of an algorithm, but not of a program. One of the main goals of this book is to convince the reader that things are not so bad.

A well-known programmer, C.A.R. Hoare, said that the beauty of a program is not an additional benefit but a criterion
...
Building Modern Web Applications Using Angular
Building Modern Web Applications Using Angular

Key Features

  • Learn about the core building blocks of Angular
  • Build and architect high performance web applications
  • Implement the latest JavaScript concepts in ECMAScript 2015, ECMAScript 2016, and TypeScript
  • Leverage the latest Angular features to get the most out of your web...
Foundations of Statistical Algorithms: With References to R Packages (Chapman & Hall/CRC Computer Science and Data Analysis)
Foundations of Statistical Algorithms: With References to R Packages (Chapman & Hall/CRC Computer Science and Data Analysis)

A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today’s more powerful statistical...

Applied Bayesian Statistics: With R and OpenBUGS Examples (Springer Texts in Statistics)
Applied Bayesian Statistics: With R and OpenBUGS Examples (Springer Texts in Statistics)

This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs  in Statistics, Biostatistics, Engineering, Economics,...

Evolutionary Computation 1: Basic Algorithms and Operators
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!)
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)
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....
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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,...

Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)
Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)

This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer-based solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions using polynomials and...

Analysis of Correlated Data with SAS and R
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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