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Deepnotes is an ongoing series of notes for a ML pipeline.
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when we develop machine learning systems for embedded (or remote) targets it is always convenient to have remote access to these machines, It will enable us to run/debug code remotely or even develop at the same time.
Reproducibility of the training variable flow can help debug and improve networks.
GStreamer as a media flow backbone to make deep learning modular and DeepStream to get the best out of nvidia's hardware capabilities.
Working with docker containers helped me to fail-recover-improve with less overhead and make things more portable. #using-can-bus-with-nvidia-agx-xavier-devices
Vehicle inter processor communication is mostly facilitated by the CAN bus. Using AGX-Xavier with the CAN bus opens many doors to create intelligent control systems.
- A PyTorch WalkThrough: Note 1
- Tensors and Data: Note 2
- Building a Network 1
- Backpropagation
- SoftMax loss and Cross Entropy loss gradient: From theory to practice
upcoming..
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