**This is a Deep Learning Institute hands-on training lab, which will require a "Conference & Training Pass." You will also need to bring your own laptop. To prepare for the lab, please follow instructions here: https://www.nvidia.com/content/dam/en-zz/Solutions/gtc/whitepages/DLI_Lab_Instructions.pdf
One important area of current research is the use of deep neural networks to classify or forecast time-series data. Time-series data is produced in large volumes from sensors in a variety of application domains including Internet of Things (IoT), cyber security, data center management and medical patient care. In this lab, you will learn how to create training and testing datasets using electronic health records in HDF5 (hierarchical data format version five) and prepare datasets for use with recurrent neural networks (RNNs), which allows modeling of very complex data sequences. You will then construct a long-short term memory model (LSTM), a specific RNN architecture, using the Keras library running on top of Theano to evaluate model performance against baseline data.