If you are interested in math and neural networks, it is impossible that you haven’t heard of Kullback-Leibler Divergence or KL-Divergence as it is popularly called in the deep learning community. It plays a pivotal role, especially in Generative Adversarial Networks (GANs). While the definition and equation seem pretty straightforward, I have a question.
Did Brene Brown lie or am I taking it too seriously?
I literally don’t know how to rejoice in the unquantifiable and only feel progress if I “measure what matters”. Professional life has f*cked me…