## Using TensorFlow’s Batch Normalization Correctly

The TensorFlow library’s layers API contains a function for batch normalization: tf.layers.batch_normalization. It is supposedly as easy to use as all the other tf.layers functions, however, it has some pitfalls. This post explains how to use tf.layers.batch_normalization correctly. It does not delve into what batch normalization is, which can be looked up in the paper “Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift” by Ioeffe and Szegedy (2015). Continue reading Using TensorFlow’s Batch Normalization Correctly

## Connecting PyCharm to a TensorFlow Docker Container

This guide walks you through setting up PyCharm Professional and Docker, with the goal of developing TensorFlow applications in PyCharm, while executing the code inside of an encapsulated container. After completing the following steps, you will be able to write Python code in PyCharm, and have the execution take place on a container, without any complication. Continue reading Connecting PyCharm to a TensorFlow Docker Container