Randall Lin

Lead ML Engineer, Labelbox

  • About
  • Sessions

With experience in large scale NLP on TPUs using limited labeled data and quick iterative ML experimentation tooling with Airflow and Kubernetes, Randall is currently envisioning the future of a training data platform with Labelbox.

Urban Air Land Mobility Project with Labelbox

Stanford masters students as part of CS230: Deep Learning describe the process and workflows for their project in which they focus on identifying suitable areas to land urban air vehicles through satellite imagery. In the recap, Andrew and Seraj share their experience completing image segmentation tasks via Labelbox’s software and labeling service, as well as lessons learned and best practices for other computer vision researchers.

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