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  <title><![CDATA[ML@GT Seminar Series Wednesday Sep 6 2017, 12:30 pm - 1:30 pm  Location: Marcus Nanotechnology Building, Room 1118]]></title>
  <body><![CDATA[<p><strong>Abstract:</strong>&nbsp;In this talk, you will get an exposure to the various types of deep learning frameworks&nbsp;&ndash; declarative and imperative frameworks such as TensorFlow and PyTorch. After a broad&nbsp;overview of frameworks, you will be introduced to the PyTorch framework in more detail. We&nbsp;will discuss your perspective as a researcher and a user, formalizing the needs of research&nbsp;workflows (covering data pre-processing and loading, model building, etc.). Then, we shall see&nbsp;how the different features of PyTorch map to helping you with these workflows.</p>

<p><strong><sup>__________________________</sup></strong></p>

<p><strong>Bio:</strong>&nbsp;Soumith Chintala is a Researcher at Facebook AI Research, where he works on deep&nbsp;learning, reinforcement learning, generative image models, agents for video games and large-scale high-performance deep learning.&nbsp;With over&nbsp;500 commits,&nbsp;Soumith is also one of the&nbsp;primary developers&nbsp;of the popular open-source PyTorch framework for deep learning.&nbsp;Prior to joining Facebook in August 2014, he worked at MuseAmi, where he built deep learning&nbsp;models for music and vision targeted at mobile devices. He holds a Masters in CS from NYU, and&nbsp;spent time in Yann LeCun&rsquo;s NYU lab building deep learning models for pedestrian detection,&nbsp;natural image OCR, and&nbsp;depth-images among others.</p>
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