Loading patent…
OwnerNicholas PRAYOGO, Syed Salman ALI +4inventors
InventorsNicholas PRAYOGO, Syed Salman ALI, Ehsan AMJADIAN, Steven ZHANG, Brijesh JETHVA, Danny HUI
Estimating the term…
Methods, systems, and techniques for applying machine learning in a hybrid cloud computing environment. A request to perform a forecasting task is received at a private cloud endpoint. The task may be, for example, a sequential forecasting task such as volume forecasting or anomaly detection based on historical log data. A proxy is used to route the request to a trained machine learning model running in a public cloud by connecting the private cloud endpoint to the public cloud endpoint. The proxy can also select one of multiple public clouds and one of multiple trained machine learning models to which the request is routed.
A method of applying machine learning in a hybrid cloud computing environment for forecasting, the method comprising:
A system for applying machine learning in a hybrid cloud computing environment for forecasting, the system comprising:
At least one non-transitory computer readable medium having stored thereon computer program code that is executable by at least one processor, wherein when executed the computer program code causes the at least one processor to perform a method of applying machine learning in a hybrid cloud computing environment for forecasting, the method comprising:
Dependencies are inferred from the claim text.