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Using MATLAB with Tensorflow and PyTorch for Deep Learning

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Published on 12/17/22 / In How-to & Learning

Watch live to learn about how the deep learning frameworks in MATLAB and Simulink can be used with TensorFlow and PyTorch to provide enhanced capabilities for building and training your Machine Learning model.

Heather Gorr, PhD and Yann Debray will show you can take full advantage of the MATLAB ecosystem and integrate it with resources developed by the open-source community. You can combine workflows that include data-centric preprocessing, model tuning, model compression, model integration, and automatic code generation with models developed outside of MATLAB.

Explore the options and benefits, along with examples, of the various interoperability pathways available, including:
- Importing and exporting models from TensorFlow, PyTorch, and ONNX into and from MATLAB
- Coexecuting MATLAB alongside installations of TensorFlow and PyTorch

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