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The Hewlett Packard Enterprise Data Science Institute at the University of Houston (UH) brings you a day long workshop on deep learning using TensorFlow.
Machine learning methods have long been employed to analyze biomedical data, from chest X-ray images to brain signals. In the past few years, large amounts of such biological and clinical data have begun to be collected at an unprecedented speed and scale. This development has rendered the previous labor-intensive methods of analysis impractical. It has become necessary to devise deep learning algorithms (implemented in GPU-accelerated computers) to allow us to scale the analyses up to such unprecedented amounts of data. Deep learning architectures have produced results comparable, and in some cases superior, to human experts. In this hands-on workshop, we will explore the deep network world (from Convolutional to Recurrent Neural Networks) using the most popular framework, TensorFlow.
TensorFlow is currently considered as among the most powerful deep learning platforms. We will demonstrate how to implement famous deep learning models (such as Neural Networks, Convolutional Neural Networks, AutoEncoder and others) to solve medical-field related prob - lems (such as X-Ray classification, cell detection etc.). In this workshop, you will learn about the basics of coding in TensorFlow and creating simple models to analyze data with deep learning techniques.