Tun Shwe
where else to find them
linkedin:tunshwe
what they talk about
all 4 in the filters
where they keep going back
no series more than once — all 5 in the filters
on a stage with
never shared a talk
who talks about the same things
- Patrick Deziel4 talks
- Eric Johnson25 talks
- Tugdual Grall21 talks
- Joe Karlsson16 talks
- Joshua Arvin Lat20 talks
- Didier Girard13 talks
| title | conference | date |
|---|---|---|
| Your Insecure MCP Server Won't Survive Production | AI Engineer Europe 2026 | 2026-04-08 |
Claims five concrete rules for secure MCP design including five core principles (shrink attack surface, schema-validated inputs, defensive docs, minimal… | ||
| Moving from Offline to Online Machine Learning with River | PyData Global 2024 | 2024-12-03 |
River claims to make online ML practical in Python by learning one observation at a time and reusing scikit‑learn–style APIs for classification, regression… | ||
| Moving from Offline to Online Machine Learning with River | PyData London 2024 | 2024-06-14 |
Claims River is a practical, pure‑Python library that lets models predict one / learn one on streaming data, lowering CPU and memory by updating on each… | ||
| Moving from Offline to Online Machine Learning with River | Berlin Buzzwords 2024 | 2024-06-09 |
River brings online ML to Python by training models on streaming data one event at a time and updating state incrementally, which cuts memory/CPU compared with… | ||
| Sketching Algorithms: Making Sense of Big Data in a Single Stroke | Conf42 Python 2024 | 2024-02-29 |
Sketching algorithms produce approximate answers orders of magnitude faster than exact queries by keeping a few kilobytes of state, processing each item in a… | ||
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