- Conference
- PyData Data science & ML
- Dates
- Oct 7, 2020 – Oct 9, 2020
- Venue
- —
- Place
- —
- Format
- Online
- Status
- Past
- Attendance
- —
- Website
- pydata.org
- Recorded
- 0 sponsors · 19 speaker appearances
- Notes
- Held online (schedule room "Online"), 7-9 Oct 2020. Recorded briefly; cancelled sessions excluded. Speakers from the conference site's speaker list; affiliations parsed from speaker profile bios (null where not stated).
Ticket prices
No ticket prices recorded
Sponsors 0
No sponsors recorded
Speakers and talks 19
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Adam Grzywaczewski | NVIDIA | Talk | RAPIDS: How to accelerate your data science pipeline by orders of magnitude | — |
| Avik Sengupta | Julia Computing | Talk | Productivity and performance in one programming language - A tour of Julia | — |
| Daan de Bruin | Pacmed | Talk | Fighting COVID with Python | — |
| Damiaan Zwietering | — | Talk | Building a coronaradar | — |
| Daniel Lee | — | Talk | Stan: why does it exist? when is it useful? why do I use it? | — |
| Dennis Ramondt | Liberty Global | Talk | Monitoring a TV streaming service with AI - from PageRank to graph convolutions | — |
| dr.ir. E.Taskesen | Ministry of Infrastructure and Water Management | Talk | Improving the data understanding part by graphical hypergeometric networks. | — |
| Ilias Sarantopoulos | Beat | Talk | Real-Time ML services: From ideation to production | — |
| Koen Vossen | TeamTV | Talk | From notebook to production using flask and heroku | — |
| Maike Fischer | ING | Talk | Productionizing an unsupervised machine learning model to understand customer feedback | — |
| Matthew Rocklin | — | Talk | Dask at Global Scale with Coiled | — |
| Matthijs Brouns | Xccelerated | Talk | 10x smaller docker containers for Data Science | — |
| Nicola Pezzotti | Philips | Talk | Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the fastMRI challenge | — |
| Nikki van Ommeren | — | Talk | Productionizing an unsupervised machine learning model to understand customer feedback | — |
| Reza Sahraeian | — | Talk | The industrial challenge of missing data | — |
| Ruben Mak | — | Talk | The causal problem of overexposure to repetitive ads: instrument variables and pymc3 | — |
| Vincent Warmerdam | — | Talk | Playing by the Rules-Based-Systems | — |
| Vladimir Osin | Signify Technology | Talk | Understanding Deep Neural Networks | — |
| Wilder Rodrigues | — | Talk | Applying Deep Learning for Object Detection from a Telecom Perspective | — |