Optimization, Pytorch, Machine Learning, Deep Learning, Tensorboard.
thus allowing us to access and evaluate arbitrary tensors. This makes it easier to build, analyze, and debug ML models. On the other hand, it also makes our model more susceptible to (sometimes accidental) insertion of suboptimal blocks of code. As we will demonstrate, knowing how to identify and