A Tour of AI technologies in time series prediction
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| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cam a22000004b 4500 | ||
| 001 | MAP20200020073 | ||
| 003 | MAP | ||
| 005 | 20230321113244.0 | ||
| 008 | 200327s2019 usa|||| ||| ||eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a922.134 | ||
| 100 | 1 | $0MAPA20200014041$aZhang, Victoria | |
| 245 | 1 | 2 | $aA Tour of AI technologies in time series prediction$cVictoria Zhang |
| 260 | $aSchaumburg (Illinois)$bSociety of Actuaries $c2019 | ||
| 300 | $a38 p. | ||
| 490 | 0 | $aInnovation and Technology | |
| 520 | $aOver 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. | ||
| 650 | 4 | $0MAPA20080611200$aInteligencia artificial | |
| 650 | 4 | $0MAPA20080586546$aNuevas tecnologías | |
| 650 | 4 | $0MAPA20130003108$aInnovación disruptiva | |
| 650 | 4 | $0MAPA20080568009$aAutomatización | |
| 650 | 4 | $0MAPA20080605674$aDesarrollo tecnológico | |
| 710 | 2 | $0MAPA20080444044$aSociety of Actuaries (United States) |