A Tour of AI technologies in time series prediction

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<rdf:Description>
<dc:creator>Zhang, Victoria </dc:creator>
<dc:creator>Society of Actuaries (United States)</dc:creator>
<dc:date>2019</dc:date>
<dc:description xml:lang="es">Sumario: Over the past few years, Artificial Intelligence (AI) technologies such as Machine Learning (ML) and Deep Neural Networks (DNN) or Deep Learning (DL) have become a very hot topic in many areas. The emerging field of DNNs was created around the concept of biological neural networks and has been widely applied in many fields. AI technologies have been used for computer vision, speech recognition, autonomous driving, etc. and have demonstrated remarkable results. McKinsey predicts that AI techniques have the potential to create between $3.5T and $5.8T in value annually across nine business functions in 19 industries. However, even with the buzzwords around for a few years, AI is still very new to the actuarial field.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/172069.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:publisher>Society of Actuaries</dc:publisher>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Inteligencia artificial</dc:subject>
<dc:subject xml:lang="es">Nuevas tecnologías</dc:subject>
<dc:subject xml:lang="es">Innovación disruptiva</dc:subject>
<dc:subject xml:lang="es">Automatización</dc:subject>
<dc:subject xml:lang="es">Desarrollo tecnológico</dc:subject>
<dc:type xml:lang="es">Libros</dc:type>
<dc:title xml:lang="es">A Tour of AI technologies in time series prediction</dc:title>
<dc:format xml:lang="es">38 p.</dc:format>
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