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<p><span style="font-size:11.5pt;font-family:"Arial",sans-serif;color:#212121">At tonight’s (10/3</span><span style="font-size:11.5pt;font-family:"Arial",sans-serif;color:#1F497D">1</span><span style="font-size:11.5pt;font-family:"Arial",sans-serif;color:#212121">)
 meeting we will have a presentation from one of our very own graduate students, Colton Smith. He will be talking about Reinforcement Learning; the full abstract is below. We will still be holding our study session on Thursday 6-8pm.</span><span style="font-family:"Calibri",sans-serif;color:#1F497D"><o:p></o:p></span></p>
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<p><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Abstract: We live in a day where there exist copious amounts of data on just about any topic one could want. Given this, applying this available data has become very lucrative. In
 this talk, we will discuss the field of giving computers the ability to learn from data: machine learning. Specifically, after a broad overview of the field, we will cover the technique of reinforcement learning. There will be an emphasis on high-level concepts
 and real-world applications, not on technical details, so no prior knowledge is needed for this discussion.</span><span style="font-family:"Calibri",sans-serif;color:black"><o:p></o:p></span></p>
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<p><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">Nathan Steadman</span><span style="font-family:"Calibri",sans-serif;color:black"><o:p></o:p></span></p>
<p><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:black">ACM President</span><span style="font-family:"Calibri",sans-serif;color:black"><o:p></o:p></span></p>
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