Emmanuel Tiongson

Machine learning engineer, six years, mostly applied work on documents and text rather than anything research-facing. My background is in applied mathematics and I came into this through a job doing forecasting, which is a good grounding because it teaches you early that most of the difficulty is in the data and the evaluation, not the model. Lately I have been doing more of the deployment and monitoring side, since a model nobody can retrain is a liability. I am wary of demos.