Real-time AI research: Difference between revisions
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Javier Gonzalez, [[Amazon]] <gojav@amazon.co.uk> | Javier Gonzalez Hernandez, [[Amazon]] <gojav@amazon.co.uk> | ||
Machine Learning researchers often try multiple configurations of | Machine Learning researchers often try multiple configurations of machine learning algorithms using libraries such as GPyOpt. The convergence resulting from different configurations is unknown in advance, but could be visualised in real time, while multiple alternatives run concurrently in the cloud. Your task is to create a control panel with architecture support that will allow researchers to monitor large numbers of simultaneous Python experiments, interactively shutting some down, or tweaking parameters via the user interface, in response to what they see. | ||
Latest revision as of 17:03, 8 November 2017
Javier Gonzalez Hernandez, Amazon <gojav@amazon.co.uk>
Machine Learning researchers often try multiple configurations of machine learning algorithms using libraries such as GPyOpt. The convergence resulting from different configurations is unknown in advance, but could be visualised in real time, while multiple alternatives run concurrently in the cloud. Your task is to create a control panel with architecture support that will allow researchers to monitor large numbers of simultaneous Python experiments, interactively shutting some down, or tweaking parameters via the user interface, in response to what they see.
