PyData NYC: LLM & Deep Learning Tutorials, sponsored by LastMile AI 🤖

NYC Python will be joining PyData NYC at 1177 Avenue of Americas (IBM) on Mar 13th 6:30 PM for a workshop night with Andrew Hoh (Chief Product Officer at LastMile AI) and Nick Lourie (PhD Student at NYU).

⚠️Please RSVP with PyData NYC here: https://www.meetup.com/pydatanyc/events/299507856/

🍕 Pizza and drinks sponsored by LastMile AI! Thank you!
Agenda:
Building LLM Applications in Production : 45 mins
Speaker: Andrew Hoh
Andrew Hoh is the President and Co-Founder of LastMile AI. Previously, he was a Group PM Manager at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database. He graduated with a BA in Computer Science from Dartmouth College.
Empirical Methods for Deep Learning: 30 mins
Speaker: Nick Lourie
Imagine you're working on a neural net. You come up with a great idea! Maybe the model learns better if trained on the shortest examples first. So, you order the examples, feed them to the model, evaluate it, and find... the performance got worse! Is the idea bad? Or, did you just need to tune the learning rate? Optimal design analysis (OPDA) combines an empirical theory of deep learning with statistical analyses to answer these questions.
Networking: 30 mins
Connect with fellow data enthusiasts, professionals, and community leaders. Build meaningful connections and forge collaborations.
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RSVP is required, please note that walk-ins will not be accepted.
Note: Per building policy, RSVPs will close at 12 pm on Mar 11
Doors @ 6 pm
Event @ 6:30 - 8:30 pm
Venue provided by IBM: 1177 Ave of Americas
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The building requires a government-issued photo ID for entrance.
This, and all NYC Python and PyData NYC events, is an all-levels event. Newcomers and beginners are welcome.
This, and all NumFOCUS-affiliated events and spaces, both in-person and online are governed by a Code of Conduct. More at https://pydata.org/code-of-conduct/
This event may be recorded.