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Text classification and named entity recognition with BertForTokenClassification & BertForSequenceClassification

Recognizing entities is a fundamental step towards understanding unstructured data in documents. Spark NLP includes state-of-the-art BERT-based models for token classification and sequence classification.

This session will cover the background and motivation behind these models, practical code implementations and introduce you to some of the pretrained models available in Spark NLP and its licensed counterpart, Spark NLP for Healthcare (clinical natural language processing and more).

About the speaker

Luca Martial
Data Scientist

Luca Martial is a Data Scientist at John Snow Labs. In this role, he has been building custom NLP solutions to showcase John Snow Labs’ healthcare library capabilities to customers, and training Spark NLP models for named entity recognition, relation extraction, text classification, de-identification and clinical entity resolution of medical notes and reports.