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MATLAB with TensorFlow and PyTorch for Deep Learning

Overview

MATLAB® and Simulink® with deep learning frameworks, TensorFlow and PyTorch, provide enhanced capabilities for building and training your machine learning models. Via interoperability, 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.

> Click here to see all webinars in the MATLAB with Python for AI Series

Highlights

  • Importing and exporting models from TensorFlow, PyTorch, and ONNX into and from MATLAB
  • Coexecuting MATLAB alongside installations of TensorFlow and PyTorch

About the Presenter

Dr Emmanuel Blanchard is a senior application engineer at MathWorks who first joined the company as a training engineer in 2014. He focuses on data analytics. Prior to joining MathWorks, he was a Lecturer in Mechatronic Engineering at the University of Wollongong. He holds a PhD in Mechanical Engineering from Virginia Tech. He also worked as a Systems / Controls Engineer at Cummins Engine Company and as a research assistant in several research institutions in California and Virginia. 

Dr Peter Brady is a Senior Application Engineer with MathWorks striving to accelerate our customer’s engineering and scientific computing workflows across maths, statistics, finance and machine learning. Prior to joining MathWorks, Peter worked in computational fluid and thermodynamics as well as high performance computing for a number of defence and civil contractors as well as a few universities. He has worked in fields as diverse as cavitation, wave/turbulence interactions, rainfall and runoff, nano-fluidics, HVAC and natural convection including scale out cloud simulation techniques. Peter holds doctorate in free surface computational fluid dynamics and a Bachelor of Civil Engineering both from the University of Technology Sydney and is a Chartered Practicing Engineer in Australia.

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