I have coded up a Deep Learning/Neural Network program.
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Zeit (absteigend)- You can import TensorFlow and PyTorch models into MATLAB. You can do that to combine preprocessing and or postprocessing algorithms in MATLAB with AI algorithm that was developed in TensorFlow or PyTorch. Or you can generate library-free C code from the imported model for deploying it to a microcontroller, ECU, or a PLC. You can also generate HDL to target FPGA or CUDA code to target a GPU. You can simulate imported models in Simulink to test how your AI model interacts with control and signal processing algorithms modeled in Simulink.
- You can also co-execute TensorFlow and PyTorch models with MATLAB algorithms by calling TensorFlow and PyTorch models from MATLAB directly. You can even use MATLAB to optimize hyperparameters of a deep learning model you are training in TensorFlow.
Just to see how it develops: about 40% of early voters voted for the 'I want to learn to' option. 'in Matlab' was 25%, with an even spread for the remainder.