Ruben Mak
where else to find them
what they talk about
where they keep going back
- PyData Eindhoven4 editions2019–2022
- PyData Amsterdam2 editions2017–2018
on a stage with
never shared a talk
who talks about the same things
- Eyal Kazin8 talks
- Michelle Frost7 talks
- Lucas Javier Bernardi4 talks
- Alon Nir5 talks
- Vincent D Warmerdam22 talks
- Aileen Nielsen7 talks
| title | conference | date |
|---|---|---|
| Is it a predictive model? Is it causal inference? Well... It is running a greenhouse. | PyData Eindhoven 2022 | 2022-12-01 |
Automation of greenhouse irrigation at Source combines concrete claims and tools: a multi stage approach first trains a predictive model of water uptake on non… | ||
| Some Attention for Attenuation Bias | PyData Eindhoven 2021 | 2021-11-12 |
The talk covers attenuation bias (measurement error/regression dilution) that shrinks model coefficients toward zero when features are noisy, and explains… | ||
| The causal problem of overexposure to repetitive ads: instrumental variables and pymc3 | PyData Eindhoven 2020 | 2020-10-07 |
Analyzes why targeted online advertising can lead to users being overexposed to repetitive ads by framing it as a causal inference problem. Uses a case study… | ||
| Advertising, algorithms and Privacy: recent opensource developments | PyData Eindhoven 2019 | 2019-11-16 |
Discusses concrete privacy wins and failures in advertising and algorithms: demonstrates reproducible de-anonymization of the Netflix Prize dataset, membership… | ||
| Thompson Sampling for Machine Learning | PyData Amsterdam 2018 | 2018-05-25 |
Overview of applying Thompson Sampling to machine learning problems, including technical examples like using Bayesian Neural Networks implemented with Edward… | ||
| Successfully Applying Bayesian Statistics to A/B Testing in Your Business | PyData Amsterdam 2017 | 2017-04-07 |
The talk examines using Bayesian statistics—especially hierarchical Bayesian models implemented with PyMC—to improve A/B testing in business. It compares… | ||
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