Conferences / PyData
PyData Cambridge 2019
Nov 15–17, 2019 · Science Centre, Anglia Ruskin University, Cambridge, United Kingdom
- Conference
- PyData Data science & ML
- Dates
- Nov 15, 2019 – Nov 17, 2019
- Venue
- Science Centre, Anglia Ruskin University
- Place
- Cambridge, United Kingdom
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- cambridgespark.com
- Recorded
- 0 sponsors · 23 speaker appearances
- Notes
- Organized/hosted by Cambridge Spark (event pages on cambridgespark.com, now redirected). Tutorials Friday, talks Saturday-Sunday. Speakers from the schedule page as archived 13 Oct 2019 (keynote titles still TBD then; the final programme may differ); affiliations as given on the schedule. Tickets sold via Eventbrite with early-bird pricing until 31 Aug 2019, but amounts were not on the archived pages. No sponsor list found.
Ticket prices
No ticket prices recorded
Sponsors 0
No sponsors recorded
Speakers and talks 23
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Ekaterina Kochmar | University of Washington | Keynote | — | — |
| Kenneth Harris | — | Keynote | — | — |
| Kirstie Whitaker | — | Keynote | — | — |
| Vishnu Anirudh | Oxbotica | Keynote | — | — |
| Betina Costa | decisionLab | Talk | We think you might like this talk: An introduction on recommendation systems | — |
| Davide Sarra | Farfetch | Talk | Practical methods to optimise model stability: case study using customer-lifetime value at Farfetch | — |
| Dom Weldon | decisionLab | Talk | Dash: Interactive Data Visualization Web Apps with no Javascript | — |
| Frank Longford | Enthought | Tutorial | Developing medical analysis tools in Python with scikit-image | — |
| Guillaume Baquiast | QuantumBlack | Talk | GA2M: combining accuracy and explainability | — |
| Ian Ozsvald | Mor Consulting | Talk | Tools for Higher Performance Python | — |
| Israel Herraiz | Tutorial | Mastering the game: reinforcement learning with Keras | — | |
| Ivan Danov | QuantumBlack | Talk | A Kedro Mindset for Data Scientists | — |
| Jacob Montiel | University of Washington | Talk | scikit-multiflow: machine learning on infinite data streams | — |
| Jaymin Mistry | PA Consulting | Talk | Using NLP to improve theatre utilisation in hospitals | — |
| Jeffrey Hsu | Scoutbee GmbH | Tutorial | A Deep Dive into NLP with PyTorch | — |
| Kevin Lemagnen | Cambridge Spark | Talk | Maintainable Code in Data Science | — |
| Kishan Manani | Farfetch | Talk | Practical methods to optimise model stability: case study using customer-lifetime value at Farfetch | — |
| Omer Yuksel | IMC | Talk | Chasing nanoseconds: data science for low-latency networks | — |
| Philip Goddard | Kindred Group | Talk | Taking your machine learning workflow to the next level using Scikit-Learn Pipelines | — |
| Raoul-Gabriel Urma | Cambridge Spark | Tutorial | Advanced Software Testing for Data Scientists | — |
| Raphael Meudec | Sicara | Talk | tf-explain: Interpretability for Tensorflow 2.0 | — |
| Robert Crowe | Talk | Taking Machine Learning Research to Production | — | |
| Stephanie Bracaloni | Iotic Labs | Talk | Tests and reliability in Machine Learning Projects | — |