Deep Neural Network implemented in pure SQL over BigQuery

Paper repro: “Self-Normalizing Neural Networks”

SNNs are really cool: their goal is to create neural networks in which, if the input of any layer is normally distributed, the output will automatically also be normally distributed. This is amazing because normalizing the output of layers is known to be a very efficient way to improve the performance of neural networks, but the current ways to do it (eg BatchNorm) basically involve weird hacks, while in SNN the normalization is an intrinsic part of the mathematics of the neural net.

Deploy Gluon models to AWS DeepLens using a simple Python API

Using Google Cloud AutoML to Classify Poisonous Australian Spiders

Google’s new Cloud AutoML Vision is a new machine learning service from Google Cloud that aims to make state of the art machine learning techniques accessible to non-machine learning experts. In this post I will show you how I was able, in just a few hours, to create a custom image classifier that is able to distinguish between different types of poisonous Australian spiders. I didn’t have any data when I started and it only required a very basic understanding of machine learning related concepts.