What we're about

This Meetup is a place for technical people to come and hear technical talks, and network with likeminded people in the Amsterdam region interested in Python. No Sales, No Recruiting, just technical talks.

We're part of the global PyData network, that promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization.

Interested in speaking or hosting a meetup? Shoot us a message at amsterdam[at]pydata.org

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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 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) or the group organizer.

Upcoming events (2)

PyData @ Heineken - Beer quality w. spectral data & Practical forecasting

Is Python your second language? If so, then we have a very exciting announcement for you! Join us on the 19th of October, from 17.30 till 22.00, at the Heineken Experience to enjoy inspiring talks and network with fellow Python enthusiasts.

During this event, we will host two talks: one providing a practical (but not just basic!) overview of forecasting methods, the other on predicting beer quality using chemical analysis data. You don’t want to miss those! Before and after the presentations, there will be an opportunity for networking while enjoying a beer and snacks.

Schedule:
[masked]: Welcome with food and drinks
[masked]: Talk 1 - Forecasting: a practical overview of methods, Tomislav Suhina
[masked]: Break
[masked]: Talk 2 – Inferring beer quality from spectral chemical data analysis, Jurgen Nijkamp
[masked]: Networking

“Forecasting: a practical overview of methods” by Tomislav Suhina
Opportunities to apply time-series forecasting are everywhere. Some examples could be planning production to meet future demand, predicting the number of visitors to make informed staffing decisions, or projecting any decision/curiosity-related quantity/kpi into the future.
There exists a truly sizeable list of algorithms implemented through various open-source packages at our disposal, ready to help us in various forecasting tasks, each with their own strengths, weaknesses, and compromises. Decision on when to use what is not always simple.
In this talk, I'll use toy datasets to share some of my learnings on different (simulated) forecasting scenarios, with each scenario having its own set of challenges and limitations.

“Inferring beer quality from spectral chemical data analysis” by Jurgen Nijkamp
Heineken has a long history of quality control for beer. Our flagship beer is regularly tested and compared across breweries to ensure it tastes the same, no matter where you buy it. The quality is evaluated using both chemical analysis and via a panel of trained testers. This talk highlights the use of machine learning on spectral chemical analysis data to infer beer quality and the drivers that make beer age well.

PyData Global 2022 (GLOBAL ONLINE CONFERENCE)

Network event

Link visible for attendees

The PyData Global Online Conference is where users, contributors, and newcomers can share experiences to learn from one another and grow together. PyData provides a virtual 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.
This three-day online event consists of talks, tutorials, and discussions to bring attendees the latest project features along with cutting-edge use cases.
The time span of the conference stretches beyond any single time zone, reflecting the global nature of our community. To accommodate our attendees, each session will be recorded and made available to attendees the following day. Following the Conference, all recordings will be posted to the PyData YouTube channel.

Tickets follow a pay-what-you-can model and can be found here: https://pydata.org/global2022/tickets/

Why Charge for an Online Conference?

Revenue from the event will go to PyData and NumFOCUS, a nonprofit organization that supports open source scientific computer programming. NumFOCUS currently sponsors 43 Open Source Projects, and organizes community-driven educational programs for users and developers of open source scientific tools.
While the 2022 PyData Global Conference has no costs for venue or catering, there are still costs associated with bringing the event online. We also need to continue paying fixed costs to keep NumFOCUS healthy, as well as continue supporting the open source community.
For this reason, we have chosen to sell tickets with a pay-what-you-can pricing model. We appreciate your support for us during this time so that we can keep supporting you in the future.

Past events (58)

Machine Learning in Production

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