Gaussian kernel transform — input distribution through NPN to output I found that picking the right activation function for a Bayesian Neural Network lets you compute uncertainty analytically in a single forward pass instead of running 50 Monte Carlo samples. 18x faster inference. The math works because Gaussian-family distributions have closed-form moments under exponential-quadratic activations,
TL;DR: Copy & paste the linked code to have working Neural Network as a starting point for your application Introduction I tried several times to get started with Deep Learning. But pretty much all the tutorials were outdated and it was just a lot of work with no result in the end. This time I
TL;DR: Get free a GPU and environment with Jupyter Notebook with this tutorial I always struggle to set up the environment for deep learning frameworks. It seems you need the right set and versions of hardware, OS, drivers,framework. And if you want GPU support, things get even worse. But google wants you to use their google