Contents tagged with Tensorflow
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Evolution of Machine Learning, from Server to the Edge App Development
Traditionally, Machine Learning (ML) and Deep Learning (DL) models were implemented within an application in a server-client fashion way. The server provided training and inference capabilities by exposing web APIs of any sort (REST, web-socket, PUB/SUB, etc…) while the client was used mainly to exchange data with the server and present the inference result to the user. Whilst this approach has been proven to work well in many cases, it involves a lot of Input/Output (I/O) and a subsequent slowdown of the application.