CPC G06F 3/0679 (2013.01) [G06F 3/0604 (2013.01); G06F 3/067 (2013.01); G06F 3/0608 (2013.01); G06F 3/0646 (2013.01); G06F 3/0649 (2013.01); G06F 9/4881 (2013.01); G06F 9/5027 (2013.01); G06F 16/1794 (2019.01); G06F 16/245 (2019.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06Q 30/0243 (2013.01); G06T 1/20 (2013.01); G06T 1/60 (2013.01); G06F 16/248 (2019.01); G06F 16/972 (2019.01); G06T 2200/28 (2013.01)] | 20 Claims |
1. A method comprising:
storing, within one or more storage systems, a transformed dataset generated by applying one or more transformations to a dataset that are identified based on one or more expected input formats of data received as input data by one or more machine learning models to be executed on one or more servers; and
transmitting, from the one or more storage systems to the one or more servers without reapplying the one or more transformations on the dataset, the transformed dataset including data in the one or more expected formats of data to be received as input data by the one or more machine learning models.
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