Learning Bayesian Models with R
Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems
About This Book
Understand the principles of Bayesian Inference with less mathematical equations
Learn state-of-the art Machine Learning methods
Environmental Foresight and Models: A Manifesto
Policy-makers and the public, it has famously been said, are more interested in the possibility of non-linear dislocations and surprises in the behaviour of the environment than in smooth extrapolations of current trends. The International Task Force in Forecasting Environmental Change (1993-1998) dedicated its work to developing procedures...
Environmental Chemistry and Toxicology of Mercury
The book that looks at mercury's impact on the planet today
Recent research by the EPA has concluded that one in six women of childbearing age have unsafe levels of mercury in their bodies, which puts 630,000 newborn babies each year at risk of neurological impairment. Mercury poses severe risks to the health of animals and...
Modeling the Internet and the Web: Probabilistic Methods and Algorithms The World Wide Web is growing in size at a remarkable rate. It is a huge evolving system and its data are rife with uncertainties. Probability and statistics are the fundamental mathematical tools that enable us to model, reason and infer meaningful results from such data. Modelling the Internet and the Web covers the...
Coping with Uncertainty: Modeling and Policy Issues Uncertainties and risks have always been, and will remain, present; both in everybody’s life and in policy making. This presence is not always recognized because humans tend to perceive the world in a deterministic way, and in most cases succeed in somehow dealing with uncertainties. However, ignoring uncertainties often results in serious...
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