Vores kunder ligger øverst på Google

Google Ads Specialister fra Vestjylland

Vi er 100% dedikerede til Google Annoncering – Vi har mange års erfaring med Google Ads og den bruger vi på at opsætte, optimere & vedligeholde vores fantastiske kunders konti.

100% Specialiseret i Google Ads
Vi har mange års erfaring fra +300 konti
Ingen lange bindinger & evighedskontrakter
Jævnlig opfølgning med hver enkelt kunde
Vi tager din virksomhed seriøst
KONTAKT OS
LÆS UDTALELSER & SUCCESHISTORIER

3 results (0,14369 seconds)

Show all filters

Brand

Merchant

Price (EUR)

Reset filter

Products
From
Shops

Clean Numerical Simulation

Clean Numerical Simulation

This book describes the basic principles of Clean Numerical Simulation (CNS) proposed by the author in 2009 as well as several of its applications. Unlike conventional algorithms CNS gives in a sufficiently long interval of time a convergent chaotic trajectory whose numerical noise is much lower than the true physical solution so that one can gain accurately. Thus CNS provides for the first time an ability to check statistics stability of chaos leading to a completely new concept of ultra-chaos which has both trajectory instability and statistics instability and thus is of a higher disorder. Notably it is impossible to repeat experimental results of ultra-chaos even in the statistical sense. However the reproducibility of physical experiments forms a cornerstone for modern science. Thus ultra-chaos reveals an incompleteness of the modern science paradigm. In addition it also reveals statistics stability as a precondition for use of conventional algorithms including direct numerical simulation (DNS). In Clean Numerical Simulation several conjectures and open problems are proposed including a modified fourth Clay millennium problem. Indeed CNS opens the door for us to enter the clean numerical world of chaos and turbulence.

GBP 74.99
1

Simple Extensions with the Minimum Degree Relations of Integral Domains

Simple Extensions with the Minimum Degree Relations of Integral Domains

Although there are many types of ring extensions simple extensions have yet to be thoroughly explored in one book. Covering an understudied aspect of commutative algebra Simple Extensions with the Minimum Degree Relations of Integral Domains presents a comprehensive treatment of various simple extensions and their properties. In particular it examines several properties of simple ring extensions of Noetherian integral domains. As experts who have been studying this field for over a decade the authors present many arguments that they have developed themselves mainly exploring anti-integral super-primitive and ultra-primitive extensions. Within this framework they study certain properties such as flatness integrality and unramifiedness. Some of the topics discussed include Sharma polynomials vanishing points Noetherian domains denominator ideals unit groups and polynomial rings. Presenting a complete treatment of each topic Simple Extensions with the Minimum Degree Relations of Integral Domains serves as an ideal resource for graduate students and researchers involved in the area of commutative algebra.

GBP 180.00
1

Data Science and Analytics with Python

Data Science and Analytics with Python

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python such as SciKit-learn Pandas Numpy and others. The use of Python is of particular interest given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are from the point of view of the process and results obtained. Important features of Python are also covered including a Python primer. The basic elements of machine learning pattern recognition and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python clustering techniques and classification algorithms are covered in the second part of the book. Hierarchical clustering decision trees and ensemble techniques are also explored along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book. About the Author Dr. Jesús Rogel-Salazar is a Lead Data scientist with experience in the field working for companies such as AKQA IBM Data Science Studio Dow Jones and others. He is a visiting researcher at the Department of Physics at Imperial College London UK and a member of the School of Physics Astronomy and Mathematics at the University of Hertfordshire UK He obtained his doctorate in physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant in the financial industry since 2006. He is the author of the book Essential Matlab and Octave also published by CRC Press. His interests include mathematical modelling data science and optimization in a wide range of applications including optics quantum mechanics data journalism and finance.

GBP 52.99
1