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About __orange

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  1. For graphics cards, AIO water cooling cards are recommended if you have enough space to mount radiators. Radial fan cooling card is second choise. Never use axial fan colling card in multi-card setup.
  2. Jetson Nano is designed for edge inferencing. It is not needed for deep learning (it is only for deploying). You still need a CUDA device for training. Just buy a nvidia (gaming) graphics card which fit your budget. Titan V/Titan RTX is fine but too expensive. Better to choose 2x RTX2080Ti. GTX graphics cards (without tensor cores) are also good if you can't afford a RTX2060. For edge inferencing device like Jetson Nano, there are: Raspberry Pi, Kirin 970/980, Hisilicon Hi3559a, NextVPU N171, Rockchip RK3399Pro/RK1808, Snapdragon 845/850, etc... Do NOT buy if your are not familiar with them. RX480 can be used for deep learning. There is a framework called ROCm. But it is not the first choice.