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

englanti
2026-05-31
49,74 € 76,52 €

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Toimitus 10-16 arkipäivässä

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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 ... Täydellinen kuvaus

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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. 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.

Lisätietoja

Kirjoittaja James Burridge, Nick Tosh
Julkaisija Cambridge University Press
Julkaisuvuosi 2026
Kannen tyyppi Pehmeäkantinen
EAN 9781009630726
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Arvostelet: Inference in Statistical Modelling and Machine Learning: A Concise Introduction
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49,74 € 76,52 €