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| | Learning R Programming
Key Features
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Explore the R language from basic types and data structures to advanced topics
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Learn how to tackle programming problems and explore both functional and object-oriented programming techniques
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Learn how to address the core problems of programming in R and leverage the most popular
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The Customer Rules
At a recent family gathering in my home, the grown-ups were trading stories about companies that
provide good customer service and those that don't. Out of curiosity, I asked my then twelve-year-old
granddaughter, Margot, what she thought were the most important rules for great service. Without a
moment's hesitation, she... | | Applied C# in Financial Markets (The Wiley Finance Series)This book is designed to help experienced programmers into the C# language.
It covers all the relevant concepts of C# from a finance viewpoint.
In the preparation of this book a small standalone futures and options
trading application was written to cover all of the sections of C# that are
relevant to finance and the code... | | Learning OpenCV: Computer Vision with the OpenCV LibraryLearning OpenCV puts you right in the middle of the rapidly expanding field of computer vision. Written by the creators of OpenCV, the widely used free open-source library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on the... |
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The Atomic Corporation: Rational Proposals for Uncertain TimesIn Atomic the authors' revolutionary theory is put to the test. Looking across all sectors of business, including retail banking, financial services, telecommunications, IT and consultancy, carbon-based corporations (oil and gas companies), and consumer products companies, Camrass and Farncombe discover some real eye-openers, including... | | Applied Genetic Programming and Machine Learning
This book delivers theoretical and practical knowledge on extension of Genetic Programming (GP) for practical applications. It provides a methodology for integrating Genetic Programming and machine-learning techniques. The developmentof such tools contributes to the establishment of a more robust evolutionary framework when addressing... | | Learning Classifier Systems: From Foundations to Applications
Learning classi er systems are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal di erence learning.
From the beginning, classi er systems have attracted... |
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