Overview

Do you know that the AI Systems Design Workflow can produce the best outcomes?

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

Highlights:

In this webinar, you will be able to learn,

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

Abhijit Bhattacharjee is a Principal Application Engineer at MathWorks, specializing in the areas of computer vision, audio signal processing, and machine learning. He works with clients in all industries, including consumer devices, semiconductors, government, and academics.

Prior to joining MathWorks, Abhijit was a researcher at USC Information Sciences Institute, working in programs funded by NASA and DARPA.

Projects included hyperspectral image processing and audio steganography. He holds an M.S.E.E. from the University of Southern California.

Overview

Do you know that the AI Systems Design Workflow can produce the best outcomes?

Highlights:

Register Today!

Our Speaker

Abhijit Bhattacharjee

Principal Application Engineer

MathWorks Inc.