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Spark NLP Blog

State of the Art Natural Language Processing at Scale.

John Snow Labs Releases Spark NLP 4.0, Delivering 8x Speedups, Native M1 Support, and 1,000+ New Models to the Most Used NLP Library in the Enterprise

Modern Extractive Question Answering Annotators, Notable Performance Improvements, and State-of-the-Art Models Define Spark NLP 4.0...

Automating PHI Removal from Healthcare Data With Natural Language Processing

Under the Health Insurance Portability and Accountability Act (HIPAA), minimum necessary standard, HIPAA-covered entities (such as health systems and insurers) are required to make reasonable efforts to ensure that access to...

Rule Based and Pattern Matching for Entity Recognition in Spark NLP

Finding patterns and matching strategies are well-known NLP procedures to extract information from text. Spark NLP library has two annotators that can use these techniques to extract relevant information or...

Ready-to-go Spark NLP environment in SageMaker Studio

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 Account...

End-to-End No-Code Development of NER model for Text with Annotation Lab

The video shows how to put together high quality training data, train an NER model and deploy it in production environment. All that is possible without writing a line of...