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EVENT DETAILS |
<P><STRONG>NYU students receive a discount. Please email Mina Salib at mina@nyu.edu for the code.</STRONG></P>
<P><STRONG>DAY 1 | MONDAY, OCT. 30 </STRONG><STRONG>Includes all sessions.</STRONG></P>
<P><STRONG>Session 1: Intro to Machine Learning with <A HREF="https://www.linkedin.com/in/rossfadely/" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Ross Fadely</A> of <A HREF="http://insightdatascience.com/" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Insight Data Science</A></STRONG></P>
<P>You will be introduced to some of the core concepts needed to jump into Machine Learning (ML). In addition, we will briefly discuss how teams across many different industries & verticals are using ML in practice. We will dive into some ML case studies using Python & Scikit-Learn. Finally, we will wrap up with some best practices & guidance for continued learning about ML.</P>
<P><STRONG>You'll leave with,</STRONG></P>
<UL>
<LI>An understanding of how to analyze data using machine learning algorithms.</LI>
<LI>How algorithms should be structured to make the most use of the data you have available</LI>
</UL>
<P><STRONG>Prerequisites:</STRONG> A working knowledge of Python</P>
<P><STRONG>Installation requirements:</STRONG> To live run exercises requires a laptop with Python, Numpy, Scipy, & Scikit-Learn installed.</P>
<P><STRONG>Session 2: Machine Learning for Statisticians with<A HREF="https://www.linkedin.com/in/lentzas/" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">George Lentzas</A>, Ph.D. in Machine Learning from Oxford Currently a Professor of Machine Learning at Columbia University</STRONG></P>
<UL>
<LI>TBD</LI>
</UL>
<P><STRONG>Session 3: AI in Video Games with Julian Togelius,Associate Professor of Computer Science & Engineering at New York University</STRONG></P>
<UL>
<LI>TBD</LI>
</UL>
<P><STRONG>Session 4: Intro to Deep Learning. Insturctor: TBD<BR></STRONG></P>
<UL>
<LI>TBD</LI>
</UL>
<P><STRONG>Session 5: Understanding Linear Regression & Gradient Descent. HOSTED BY</STRONG></P>
<UL>
<LI>The difference between gradient descent & stochasticgradient descent</LI>
<LI>How to use stochastic gradient descent to learn a simple linear regression model</LI>
<LI>How to put together a simple gradient descent using a cost function, allowing you to buildan algorithm for linear regression or a consistent straight line to our data</LI>
</UL>
<P><STRONG>Session 6: Combining real world & training data. HOSTED BY</STRONG></P>
<UL>
<LI>The pros & cons of training & real world data.</LI>
<LI>How to combine training & real world data to properly train & teach your algorithms</LI>
</UL>
<P><STRONG>7:00pm - 9:00PM: Future Labs AI Summit Kick Off Party</STRONG></P>
<UL>
<LI>TBD</LI>
</UL>
<P><BR></P>
<P><STRONG>DAY 2 | TUESDAY, OCT. 31</STRONG></P>
<P><STRONG>11:00am - 5:00pm</STRONG></P>
<P>Included in your ticket purchase<STRONG></STRONG>is Day 2 of the Future Labs AI Summit,<STRONG></STRONG>a full day of presentations & panels with talks from leaders in AI as well as demos from the second cohort of the AI NexusLab. See full details here<STRONG>[INCLUDE LINK]</STRONG>.</P>
<UL>
<LI>Richard Zemel,<SPAN>Cofounder & Director of Research,</SPAN>Vector Institute for Artificial Intelligence</LI>
<LI>
<DIV CLASS="display-flex align-items-center justify-center">Evan Nisselson, General Partner, LDV Capital</DIV>
</LI>
<LI>Josh Sutton,Global Head, Data & Artificial Intelligence, Publicis.Sapient</LI>
<LI>Anand Sanwal, CEO, CB Insights</LI>
<LI>Jean-Franois Gagn, CEO, ElementAI</LI>
</UL>
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