Machine Learning: A Bayesian and Optimization Perspective

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Machine Learning: A Bayesian and Optimization PerspectiveMachine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques,

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When Olivia Kavanagh finds an old manuscript and a photograph in her late grandfather's bookshop she becomes fascinated by the story of the two young girls who mystified the world

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Learning outcomes are clearly stated at the start and end of the units

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physical chemistry and biochemistry

she runs to warn her village but no one will believe her

including 'baby'

schools and hospitals)

Written in the highly successful Methods in Molecular Biology (TM) series format

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