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Blog - Natural Language Processing

Natural Language Processing ()

  Introduction Smart assistants like Amazon’s Alexa and Apple’s Siri recognize patterns in speech using Natural Language Processing, comprehend meaning and provide a meaningful response. Search engines surface relevant results...

Using machine learning and regex patters to identify and extract date information in Spark NLP TL; DR: Extracting date information from text is a common Natural Language Processing (NLP) task...

The social determinants of health (SDoH) are the non-medical factors that influence health outcomes and usually one of the hardest type of entities to extract with pre-trained clinical NLP models....
Spark NLP pipelines

Creating visualizations for analysis and reporting using Spark NLP and Spark NLP display. TL;DR: Named entity visualization is a technique for representing the results of named entity recognition (NER) in...

Use pretrained models, segment texts into words, and train custom word segmenter models with Python TL; DR: Some Asian languages don’t separate words by white space like English, and NLP...