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Inference in Statistical Modelling and Machine Learning: A Concise Introduction - James Burridge,Nick Tosh

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2026-05-31
45,91 € 76,52 €

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Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them ... Täielik kirjeldus

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Kirjeldus

Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not certain. This concise book provides a clear introduction to those tools and to the core ideas - probabilistic model, likelihood, prior, posterior, overfitting, underfitting, cross-validation - that unify them. A mixture of toy and real examples illustrates diverse applications ranging from biomedical data to treasure hunts, while the accompanying datasets and computational notebooks in R and Python encourage hands-on learning. Instructors can benefit from online lecture slides and exercise solutions. Requiring only first-year university-level knowledge of calculus, probability and linear algebra, the book equips students in statistics, data science and machine learning, as well as those in quantitative applied and social science programmes, with the tools and conceptual foundations to explore more advanced techniques.

Lisateave

Autor James Burridge, Nick Tosh
Kirjastaja Cambridge University Press
Väljalaskeaasta 2026
Kaanetüüp Pehme kaanega
EAN 9781009630726
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45,91 € 76,52 €