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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
The PyData Code of Conduct governs this meetup. To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact NumFOCUS Executive Director Leah Silen (+1 512-222-5449; [leah@numfocus.org](mailto:leah@numfocus.org)) or the group organizer.
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Upcoming events
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November Meetup: When and How to Build an AI Agent + Faster data processing!
Moderna HQ, 325 Binney St, Cambridge, MA, USđź’»Join PyData Boston for another deep dive into AI agents! This month, we'll have a talk from Pythonista Tri Dang on when and how to build an AI agent followed by a talk on how to make your data processing faster!
We currently have no food sponsor for this event! Reach out if you're able to sponsor!
RSVP is REQUIRED to attend
Do not arrive before 6:30pm!
đź“… Schedule:
6:30–7:00 — Networking
7:00–7:15 — Introduction
7:15–8:15 — Product Development: When and How to Build an AI Agent, with Tri Dang
8:15-8:30 - Break
8:30-9:15 — Optimize first, parallelize second: a better path to faster data processing with Itamar Turner-Trauring
9:15–9:30 — Wrap-upSpeaker: Tri Dang (Kyruus Health)
Title: Product Development: When and How to Build an AI Agent
Abstract: AI technologies are disrupting how we solve problems. For many companies including ours, we need to learn how to weave AI solutions into our problem space in a seamless way. This is the classic product development principle: first identifying a problem statement then using appropriate technologies to address the challenges. Without discipline, the AI hype often pushes us to do the opposite, forcefully embedding AI into a problem.Speaker: Itamar Turner-Trauring (Pythonspeed)
Title: Optimize first, parallelize second: a better path to faster data processing
Abstract: You’re processing a large amount of data with Python, and your code is too slow. One obvious way to getting faster results is adding multithreading or multiprocessing, so you can use multiple CPU cores.
Unfortunately, switching straight to parallelism is almost always premature, often unnecessary, and sometimes impossible.📍Venue provided by Moderna
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👉 https://pydata.org/code-of-conduct/⚡⚡**Speak at PyData!**⚡⚡
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đź“§ boston@pydata.org48 attendees
Past events
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