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Annotation Lab ()

Building Real-World Healthcare AI Projects from Concept to Production

by
Juan Martinez
In this Webinar, Juan Martinez from John Snow Labs and Ken Puffer from ePlus will share lessons learned from recent AI, ML, and NLP projects that have been successfully built...

An easier API for creating custom #NLP graphs with Spark NLP for Healthcare 3.5.2

by
Muhammet Santas
TFGraphBuilder annotator to create graphs for training NER, Assertion, Relation Extraction, and Generic Classifier models Default TF graphs added for AssertionDLApproach to let users train models without custom graphs New...

Ready-to-go Spark NLP environment in SageMaker Studio

by
Erdal Genc
In this article, we are going to explain how to attach a custom Spark NLP, Spark NLP for Healthcare, and Spark OCR Docker image to SageMaker Studio.   Requirements: AWS...

Supporting training of large documents, improvements for Pdf and Image annotation in Visual NER Projects, and integration with my.JohnSnowLabs.com in the Annotation Lab 3.1.0

by
Nabin Khadka
Support Training of Large documents For training a model, the memory requirement grows as the number of tasks increases in the project. The required memory is higher for projects with...

Comparison of Key Medical NLP Benchmarks — Spark NLP vs AWS, Google Cloud and Azure

by
Veysel Kocaman
Spark NLP for Healthcare comes with 600+ pretrained clinical pipelines & models out of the box and is consistently making 4–6x less error than Azure, AWS, and Google Cloud on...
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