Award-winning AI and NLP company John Snow Labs is invited for the 3rd year in a row to present at O’Reilly Strata Data New York a series of talks on applied state-of-the-art natural language processing.
The first session is Feature engineering with Spark NLP to accelerate clinical trial recruitment – presented by Saif Addin Ellafi, Spark NLP lead at John Snow Labs, and Scott Hoch, former lead data scientist at Deep6.ai and founder of Blackbox Engineering. This session is a deep dive into the NLP case study that describes how Deep6.ai uses the Spark natural language processing (NLP) platform to apply state-of-the-art deep learning to accurately extract relevant clinical facts from unstructured text.
John Snow Labs’ Spark Healthcare NLP is a software library for Python, Java, and Scala that provides natural language understanding capabilities with state-of-the-art accuracy, performance, and scale. It provides deep learning-based NLP algorithms for named entity recognition, spell checking, sentiment analysis, assertion status detection, entity resolution, optical character recognition (OCR), and sentence segmentation, and it enables highly efficient training of domain-specific machine learning and deep learning NLP clinical and biomedical models.
The session will explain how Deep 6 uses Spark NLP for Healthcare for feature engineering that powers its clinical trial matching & ranking solution. It will cover why the system scales, for both training and inference, to millions of patients while achieving state-of-the-art accuracy. They explore the technical challenges, the architecture of the full solution, and the lessons learned that you can directly apply to your next natural language understanding project.
In addition, the highly popular half-day tutorial Natural language understanding at scale with Spark NLP is returning to Strata Data NYC – fully updated to reflect the latest advances in Spark NLP. Alex Thomas, Saif Addin Ellafi, Claudiu Branzan, and David Talby will walk through state-of-the-art natural language processing (NLP) using the highly performant, highly scalable open source Spark NLP library. This is a hands-on tutorial that enables you to run and extend executable code examples as you learn to build advanced NLP pipelines for common real-world use cases.