Fashion-MNIST exploring using Keras and Edward

Overview

On the article, Fashion-MNIST exploring, I concisely explored Fashion-MNIST dataset.

We can get access to the dataset from Keras and on this article, I’ll try simple classification by Edward.

Simple Baysian Neural Network with Edward

Overview

Edward can enable us to convert TensorFlow code to Baysian one. I’m not used to Edward. So for the training, I’m tackling with converting some TensorFlow code to Edward one. On this article, I tried to convert simple neural network model to Baysian neural network one.

The purpose of this article is to convert the TensorFlow code I posted before to Baysian one by Edward.

Baysian neural network model

By Edward, we can relatively easily convert the model using TensorFlow to probabilistic one.
The regression model for iris data is from the article below.

Simple regression model by TensorFlow

Neural network is composed of input, hidden and output layers. And the number of hidden layers is optional. So the simplest network architecture has just one hidden layer. On this article, I'll make the simplest neural network for regression by TensorFlow.

In a nutshell, the model is to predict one target value from three features. About the details, please check the article.

Simple regression by Edward: variational inference

Overview

Edward is one of the PPL(probabilistic programming language). This enables us to use variational inference, Gibbs sampling and Monte Carlo method relatively easily. But it doesn’t look so easy. So step by step, I’ll try this.

On this article, simple regression, tried on the article Simple Bayesian modeling by Stan, can be the nice example. So I did same things by Edward, using variational inference.