Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/807
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dc.contributor.authorPerrier, Alexis-
dc.date.accessioned2026-07-07T06:45:44Z-
dc.date.available2026-07-07T06:45:44Z-
dc.date.issued2017-04-
dc.identifier.issn978-1-78588-323-1-
dc.identifier.urihttp://hdl.handle.net/123456789/807-
dc.description.abstractBig data and artificial intelligence are ubiquitous part of our everyday lives, fostering a rising, billion-dollar, cloud-based Machine Learning as a Service (MLaaS) industry. Among the several Machine Learning as a Service platforms currently on the market, Amazon Machine Learning stands out for its simplicity. Amazon Machine Learning was launched in April 2015 with a clear goal of lowering the barrier to predictive analytic by offering a service accessible to companies without the need for highly skilled technical resources, while balancing performance and costs. When combined with the depth of the AWS ecosystem, the Amazon Machine Learning platform makes predictive analytics a natural element of the business data pipeline.en_US
dc.language.isoenen_US
dc.publisherPackt Publishingen_US
dc.relation.ispartofseries1210417;-
dc.subjectEffective Amazon Machine Learningen_US
dc.titleEffective Amazon Machine Learningen_US
dc.title.alternativeMachine learning in the Clouden_US
dc.typeBooken_US
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