I wouldn’t expect DropConnect to appear in TensorFlow, Keras, or Theano since, as far as I know, it’s used pretty rarely and doesn’t seem as well-studied or demonstrably more useful than its cousin, Dropout. However, there don’t seem to be any implementations out there, so I’ll provide a few ways of doing so. Continue reading “DropConnect Implementation in Python and TensorFlow”
“A Neural Algorithm of Artistic Style” is an accessible and intriguing paper about the distinction and separability of image content and image style using convolutional neural networks (CNNs). In this post we’ll explain the paper and then run a few of our own experiments.
To begin, consider van Gogh’s “The Starry Night”: Continue reading “Style Transfer with Tensorflow”
The purpose of this quick tutorial is to get you a very big, very useful neural network up and running in just a few hours. The goal is that anyone with a computer, some free time, and little-to-no knowledge of what neural networks are or how they work can easily begin playing with this technology as soon as possible. Technical explanations of what RNNs are abound on the internet, so this tutorial will skip explanation and focus solely on building. Continue reading “Building a Recurrent Neural Network to Generate Novel Text”