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IFT6266 - H2017 Deep Learning

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IFT6266 - H2017 Deep Learning

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IFT6266 - H2017 Deep Learning | A Graduate Course Offered at Université de Montréal Skip to content IFT6266 – H2017 Deep Learning A Graduate Course Offered at Université de Montréal Menu Overview Lectures Announcements Student Forum Project Description Project Blogs and Repos Questions & Answers Overview This is a course on representation learning in general and deep learning in particular. Deep learning has recently been responsible for a large number of impressive empirical gains across a wide array of applications including most dramatically in object recognition and detection in images and speech recognition. In this course we will explore both the fundamentals and recent advances in the area of deep learning. Our focus will be on neural network-type models including convolutional neural networks and recurrent neural networks such as the LSTM. We will also consider some probabilistic graphical models, including undirected models such as the Boltzmann mac...

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