Difference between revisions of "Machine learning"

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(Created page with "'''Machine learning''' ('''ML''') is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task withou...")
 
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# Although ML algorithms appeared decades ago, SEG members started publishing about them in the mid-90s. In 2019, in response to "the digital transformation of Oil and Gas" the [https://www.aapg.org/ AAPG], [https://seg.org SEG] & [https://www.spe.org/en/ SPE] decided to organize the first conference fully dedicated to the topic: "[https://energyindata.org/Default.aspx?TabId=37&language=en-US Energy in Data]"
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Although ML algorithms appeared decades ago, SEG members started publishing about them in the mid-90s. In 2019, in response to "the digital transformation of Oil and Gas" the [https://www.aapg.org/ AAPG], [https://seg.org SEG] & [https://www.spe.org/en/ SPE] decided to organize the first conference fully dedicated to the topic: "[https://energyindata.org/Default.aspx?TabId=37&language=en-US Energy in Data]"
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== References ==
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<references />

Revision as of 22:44, 24 May 2019

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.[1]

ML algorithms are being used in the Oil and Gas sector for various applications:

Although ML algorithms appeared decades ago, SEG members started publishing about them in the mid-90s. In 2019, in response to "the digital transformation of Oil and Gas" the AAPG, SEG & SPE decided to organize the first conference fully dedicated to the topic: "Energy in Data"

References