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Bayesian Reasoning and Machine Learning
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Bayesian Reasoning and Machine Learning

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619,95 kr

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ProduktVarenr.PrisHandling
Bayesian Reasoning and Machine Learning9780521518147619,95 krTil butik
Bayesian Reasoning and Machine Learning9780521518147724,95 krTil butik

Produktdetaljer

Bayesian Reasoning and Machine Learning

Bayesian Reasoning and Machine Learning

David BarberBog

619,95 kr

Til butik
Varenr.:
9780521518147

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

Læs mere hos Saxo DK
Bayesian Reasoning and Machine Learning

Bayesian Reasoning and Machine Learning

David BarberMatematik og naturvidenskab

724,95 kr

Til butik
Varenr.:
9780521518147

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

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