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Automatic Differentiation with Theano

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Implementing models in machine learning and data analysis often requires a considerable effort which can span over weeks. Symbolic differentiation can be used to speed up model prototyping in a large class of models to a single day. In this tutorial we will explain how to use Theano, a Python package for symbolic differentiation. We will walk through the theory and basics of symbolic differentiation, and will implement two real world models: logistic regression and a deep net. A NumPy refresher will be given beforehand.

This talk is part of the Machine Learning Reading Group @ CUED series.

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