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This book introduces machine learning in finance and illustrates how to integrate computational tools with numerical finance with real world applications.
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This comprehensive book offers valuable insights while using a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security.
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This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant... Læs mere
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High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically... Læs mere
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Machine learning algorithms hold out extraordinary promise, but the reality is that their success depends entirely on the suitability of the data... Læs mere
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Intermediate user level
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An authority on creativity introduces readers to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans.
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Big Data and methods for analyzing large data sets such as machine learning have deeply transformed scientific practice in many fields. This Element defends an inductivist view of big data... Læs mere
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The past decade has witnessed extraordinary advances in artificial intelligence. He looks at the ways in which it has... Læs mere
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The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods.
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Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs.
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