Overview

Software interoperability is indeed a prevalent and essential concept in today's technological landscape. It refers to the integration of distinct software products, enabling users to leverage their preferred tools for different stages of their developmental workflow. This integration fosters efficiency and flexibility, allowing users to select the best-suited products.

So, what does all these mean for the MATLAB & Python users? 

Focusing on Deep Learning Interoperability as an illustration, this session would depict how MATLAB works with Tensorflow, Pytorch and ONNX.

Highlights

• What are the common interoperability challenges faced by customers and what are we doing about them.
• Workflows for model exchange, specifically focusing on what works v/s what does not with TensorFlow Converter.