Overview
Contributed to a production robotics project for Godt Levert—focused on model performance, stability, and iteration speed.
Aggregated data from multiple runs to surface failure modes and tuned the model/thresholds to improve accuracy and consistency.
Built a small analytics/BI workspace in Google Colab to visualize raw sensor/output data, compare runs, and guide model tweaks.
Outcomes
Improved ML performance via better preprocessing, thresholding, and targeted retraining using run data.
Delivered a repeatable Colab analysis notebook that the team can use to diagnose runs and validate future changes.
Documented the pipeline (data → preprocessing → inference → evaluation) so fixes and experiments are faster to ship.
Links
More materials coming soon.