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@@ -232,6 +232,7 @@ In this repository, I will share some useful notes and references about deployin
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- [Speeding up Deep Learning Inference Using TensorFlow, ONNX, and TensorRT](https://devblogs.nvidia.com/speeding-up-deep-learning-inference-using-tensorflow-onnx-and-tensorrt/)
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- [TensorRT Developer Guide](https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html)
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- [How to Convert a Model from PyTorch to TensorRT and Speed Up Inference](https://www.learnopencv.com/how-to-convert-a-model-from-pytorch-to-tensorrt-and-speed-up-inference/) [_Good_]
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- [High Performance Python: Practical Performant Programming for Humans 1st Edition- book](https://www.amazon.com/High-Performance-Python-Performant-Programming/dp/1449361595)
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## Hardware Notes for Deep Learning:
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- [Hardware for Deep Learning](https://blog.inten.to/hardware-for-deep-learning-part-3-gpu-8906c1644664)

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