This lab explores various approaches to the problem of semantic image segmentation, which is a generalization of image classification where class predictions are made at the pixel level. We use the Sunnybrook Cardiac Data to train a neural network to learn to locate the left ventricle on MRI images. In this lab, you will learn how to use popular image classification neural networks for semantic segmentation, how to extend Caffe with custom Python layers, become familiar with the concept of transfer learning and train two Fully Convolutional Networks (FCNs). Prerequisites: Basic knowledge of Convolutional Neural Networks. This lab utilizes GPU resources in the cloud, you are required to bring your own laptop.