This event will be Livestreamed here:
https://livestream.com/accounts/23925505/events/8566140

Join us for ChiPy & CRUG's Hardware Meetup. A computer hardware themed meetup on how to build a good data science machine. The talks will be about RAM, hard drives, the new m.2 & persistent memory technologies.

SPEAKERS
Parfait Gasana will kick off the meetup by providing both instructions & a script for audience members to benchmark their own hardware in both R & Python.

Brian Peterson of Heymeyer trading + investments will crack open a desktop built for modeling high-frequency time series data & discuss its components. As someone that must process far greater amounts of data that can be contained in RAM, he offers the practitioners point of view on hardware choices.

Seth Carpenter of FHLBC will discuss how & when to use Amazon Web Services (renting someone elses hardware) & how to do so using Python.

Justin Shea will discuss his recent custom build containing an AMD Threadripper 1950x processor. This newer chip contains 16 cores, offering greater performance than its Intel counterpart, at a fraction of the cost.

About Metis

Metis (thisismetis.com) accelerates careers in data science by providing full-time immersive bootcamps, evening part-time professional development courses, online resources, & corporate programs based in Seattle, New York, Chicago, & San Francisco.

Brought to you by Kaplan, Metis focuses primarily on Python, machine learning, data visualization, deep learning, big data processing, statistical foundations, & more. Students & alumni of the bootcamp program receive continuous support from our career advisors, empowering them to pursue a successful career in the fast-growing field of data science.

Learn more about us at

https://thisismetis.com/

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We do not tolerate harassment of students, staff, or visitors in any form. Sexual language & imagery is not appropriate for any event including talks, workshops, parties, & other online media. Individuals & groups that do not abide by these rules will be asked to leave and, if necessary, prohibited from future events.

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