ML-MNIST-Caffe | tutorial shows how to train from scratch LeNet CNN

ML-MNIST-Caffe is a Python library. ML-MNIST-Caffe has no bugs, it has no vulnerabilities and it has low support. However ML-MNIST-Caffe build file is not available. You can download it from GitHub.

The tools are available only in Ubuntu 16.04, not in any other Linux distribution; they are split into two parts, one running on the Ubuntu Linux host PC and another running on the Ubuntu Linux filesystem of the target board (the ZCU102 in this case), which you need to have connected through WLAN and UART cables on your local PC. :pushpin: Note: The local PC connected to the board does not need to have the Ubuntu 16.04 OS: it could also mount the Windows OS. You only need that PC to communicate with the target board. On the other hand, the host PC must be an Ubuntu 16.04 one, be it either your local PC (mounting Ubuntu OS) or the AWS remote server. The Xilinx DNNDK tools on the host are not connected with Vivado Design Suite, because they are required for pruning and quantization. The three tools in question are decent, dnnc, and deephi_compress. This last one is not included in this tutorial because it requires a license fee, but log files are provided to illustrate how it works.