How to plot accuracy and loss with mxnet - PyImageSearch

When it comes to high-performance deep learning on multiple GPUs (and not to mention, multiple machines) I tend to use the mxnet library. Part of the Apache Incubator, mxnet is a flexible, efficient, and scalable library for deep learning (Amazon even uses it in their own in-house deep learning). Inside the ImageNet Bundle of my book, Deep Learning for Computer Vision with Python, we use the mxnet library to reproduce the results of state-of-the-art publications and train deep neural networks on the massive ImageNet dataset, the de facto image classification benchmark (which consists of 1.2 million images). As scalable as mxnet is, unfortunately it misses some of the convenience functions we may find in Keras, TensorFlow/TensorBoard, and other deep learning libraries. One of these convenience methods mxnet misses is plotting accuracy and loss over time.