Elements of causal inference

SCHOLKOPF, BERNHARD (Autor) Livro de Bolso em Inglês
    Elements of causal inference_0
    Elements of causal inference
    • Detalhes do artigo
    • Garanties
    • Acessórios incluídos
    • 3 novos desde 46,35 €  
    • Todas as ofertas
      • 46,35 € Custos de envio +0 €
        Disponível
        Novo
        Pro
        PbshopUK
        (29531)
      • 60,69 € Custos de envio +0 €
        Disponível
        Novo
        Pro
        DodaxEU-PT
        (32298)
      • 65,78 € Custos de envio +4,99 €
        Disponível
        Novo
        Pro
        MplusL
        (1084)
    • Satisfeito
      ou reembolsado
    • Levantamento
      gratuito em loja
    • Pagamentos
      Seguros
    • Devoluções
      gratuitas em loja

    Resumo Elements of causal inference

    A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.

    The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.

    After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem.

    The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

    Características detalhadasElements of causal inference

    CARACTERÍSTICAS DO EBOOK

    QUE FORMATO PARA O MEU EBOOK?

    OPINIÕES DOS NOSSOS CLIENTES Elements of causal inference

    Condições de Utilização

    Ver também