Meet us at the AI4 2022, August 16/18, MGM Grand Las Vegas at Booth #202. Schedule a meeting today here.
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Data Curation ()

Lessons Learned Applying NLP to Create a Web-Scale Knowledge Graph

High-quality Knowledge Graphs still mostly rely on structured data curated by humans. Such reliance on human curation is a major obstacle to the creation of a comprehensive, always-up-to-date knowledge graph...

Collaborative Healthcare NLP: Customisable NLP platforms for health and related research

For many years, the NLP healthcare application development are driven by NLP engineers. The engineers-centred healthcare NLP unintentionally creates barriers among healthcare workers and slows the deployment of NLP in...

Building Reproducible Evaluation Processes for Spark NLP Models

Healthcare organizations can face numerous challenges when developing high-quality machine learning models. Data is often noisy and unstructured, and developing successful models involves experimenting with numerous parameter configurations, datasets, and...

End-to-End No-Code Development of AI Models for Text and Images

AI models and pipelines for text and image processing are currently used in intelligent applications on all verticals, from Healthcare to Finance and Security. Up until now, they have been...

Cleanlab: Making AI Work with Messy, Real-World Healthcare and NLP Data

I’ll start the talk with an overview of cleanlab 2.0, a powerful open-source package that lets you find and fix label errors and data quality issues in *any* labeled dataset…...