Pesquisa de referências

What are you grouping for?

<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
  <record>
    <leader>00000cab a2200000   4500</leader>
    <controlfield tag="001">MAP20200024200</controlfield>
    <controlfield tag="003">MAP</controlfield>
    <controlfield tag="005">20220911211140.0</controlfield>
    <controlfield tag="008">200717e20200701gbr|||p      |0|||b|eng d</controlfield>
    <datafield tag="040" ind1=" " ind2=" ">
      <subfield code="a">MAP</subfield>
      <subfield code="b">spa</subfield>
      <subfield code="d">MAP</subfield>
    </datafield>
    <datafield tag="084" ind1=" " ind2=" ">
      <subfield code="a">6</subfield>
    </datafield>
    <datafield tag="100" ind1=" " ind2=" ">
      <subfield code="0">MAPA20200016380</subfield>
      <subfield code="a">Hu, Sen </subfield>
    </datafield>
    <datafield tag="245" ind1="1" ind2="0">
      <subfield code="a">What are you grouping for?</subfield>
      <subfield code="c">Sen Hu, Adrian O'Hagan</subfield>
    </datafield>
    <datafield tag="520" ind1=" " ind2=" ">
      <subfield code="a">Machine learning has increasingly become a tool for actuaries in the era of big data, and the idea of actuaries teaming up with data scientists has been continually debated by industry leaders. In a nutshell, machine learning is a sub-stream of artificial intelligence, and provides suites of algorithms and models for computers to learn from data, so that they can help find data patterns and therefore make inferences, decisions or predictions.</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080568009</subfield>
      <subfield code="a">Automatización</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080579258</subfield>
      <subfield code="a">Cálculo actuarial</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20140022717</subfield>
      <subfield code="a">Big data</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080611200</subfield>
      <subfield code="a">Inteligencia artificial</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080553128</subfield>
      <subfield code="a">Algoritmos</subfield>
    </datafield>
    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080578848</subfield>
      <subfield code="a">Análisis de datos</subfield>
    </datafield>
    <datafield tag="700" ind1=" " ind2=" ">
      <subfield code="0">MAPA20170005438</subfield>
      <subfield code="a">O'Hagan, Adrían</subfield>
    </datafield>
    <datafield tag="773" ind1="0" ind2=" ">
      <subfield code="w">MAP20200013259</subfield>
      <subfield code="t">The Actuary : the magazine of the Institute & Faculty of Actuaries</subfield>
      <subfield code="d">London :  Redactive Publishing, 2019-</subfield>
      <subfield code="g">01/07/2020 Número 6 - julio 2020 , p. 32-33</subfield>
    </datafield>
  </record>
</collection>