Continuous Data Pipeline for Real time Benchmarking & Data Set Augmentation | Teleskope

ABOUT THE TALK:
Building and curating representative datasets is crucial for accurate ML systems. Monitoring metrics post-deployment helps improve the model. Unstructured language models may face data shifts, leading to unpredictable inferences. Open-source APIs and annotation tools streamline annotation and reduce analyst workload.

This talk discusses generating datasets and real-time precision/recall splits to detect data shifts, prioritize data collection, and retrain models.

ABOUT THE SPEAKER:
Ivan Aguilar is a data scientist at Teleskope focused on building scalable models for detecting PII/PHI/Secrets and other compliance related entities within customers' clouds. Prior to joining Teleskope, Ivan was a ML Engineer at Forge.AI, a Boston based shop working on information extraction, content extraction, and other NLP related tasks.

ABOUT DATA COUNCIL:
Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

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