Machine Learning Model Portability Standard

What is the machine learning model portability standard that allows model development on commodity hardware but deployment on enterprise servers?

A. ONNX (Open Neural Network Exchange)

B. TensorFlow

C. PyTorch

Answer:

The machine learning model portability standard that allows model development on commodity hardware but deployment on enterprise servers is ONNX (Open Neural Network Exchange).

ONNX, or Open Neural Network Exchange, is an open-source model interchange format designed to facilitate interoperability between different deep learning frameworks. This standard enables developers to train and build machine learning models on their local machines using various frameworks such as TensorFlow or PyTorch, and then seamlessly deploy these models on more powerful enterprise servers for production use.

By adopting ONNX as a portability standard, developers can ensure that their machine learning models can be developed and tested on commodity hardware, while also being easily transferred and used on high-performance servers in enterprise environments. This flexibility and compatibility make ONNX a valuable tool in the field of machine learning model deployment.