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  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630725 / 9781009630726

    • Tapa blanda

    Librería: Rarewaves USA, HEBRON, KY, Estados Unidos de AmericaRarewaves USA

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 53,36

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    Se envía dentro de Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Paperback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630725 / 9781009630726

    • Tapa blanda

    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 56,55

     Gastos de envío gratis 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Paperback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630725 / 9781009630726

    • Tapa blanda

    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 64,79

    Envío por EUR 14,53 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Paperback. Condición: Brand New. 323 pages. 7.00x0.67x10.00 inches. In Stock.

  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630725 / 9781009630726

    • Tapa blanda

    Librería: Rarewaves USA United, HEBRON, KY, Estados Unidos de AmericaRarewaves USA United

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 55,48

    Envío por EUR 43,89 
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    Cantidad disponible: Más de 20 disponibles

    Paperback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630687 / 9781009630689

    • Tapa dura

    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

    Vendedor de 4 estrellas
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    Condición: Nuevo

    EUR 132,92

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    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630725 / 9781009630726

    • Tapa blanda

    Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 54,78

    Envío por EUR 75,58 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Paperback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630687 / 9781009630689

    • Tapa dura

    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 165,73

     Gastos de envío gratis 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Hardback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630687 / 9781009630689

    • Tapa dura

    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 177,37

    Envío por EUR 14,53 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Hardcover. Condición: Brand New. 323 pages. 7.00x0.75x10.00 inches. In Stock.

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630687 / 9781009630689

    • Tapa dura

    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

    Vendedor de 4 estrellas
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    Condición: Nuevo

    EUR 192,02

    Envío por EUR 3,50 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 4 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Cambridge University Press, GB, 2026

    1009630687 / 9781009630689

    • Tapa dura

    Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 161,93

    Envío por EUR 75,58 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Hardback. Condición: New. 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. Toy and real examples illustrate 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 solutions to all the exercises. 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.…

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630725 / 9781009630726

    • Tapa blanda
    • Impresión bajo demanda

    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 53,20

    Envío por EUR 14,53 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Paperback. Condición: Brand New. 323 pages. 7.00x0.67x10.00 inches. In Stock. This item is printed on demand.

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630687 / 9781009630689

    • Tapa dura
    • Impresión bajo demanda

    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

    Vendedor de 4 estrellas
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    Condición: Nuevo

    EUR 199,31

    Envío por EUR 7,56 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 4 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Cambridge University Press, 2026

    1009630687 / 9781009630689

    • Tapa dura
    • Impresión bajo demanda

    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

    Vendedor de 4 estrellas
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    Condición: Nuevo

    EUR 198,51

    Envío por EUR 9,95 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 4 disponibles

    Condición: New. PRINT ON DEMAND.