State-of-the-art named entity recognition with BERT | Webinar

Автор: John Snow Labs – Healthcare AI Company

Загружено: 2020-10-26

Просмотров: 8631

Описание: Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nl...

Watch all NLP & AI webinars: https://events.johnsnowlabs.com/webinars

Deep neural network models have recently achieved state-of-the-art performance gains in a variety of natural language processing (NLP) tasks. However, these gains rely on the availability of large amounts of annotated examples, without which state-of-the-art performance is rarely achievable. This is especially inconvenient for the many NLP fields where annotated examples are scarce, such as medical text.

Named entity recognition (NER) is one of the most important tasks for the development of more sophisticated NLP systems. In this webinar, we will walk you through how to train a custom NER model using BERT embeddings in Spark NLP – taking advantage of transfer learning to greatly reduce the amount of annotated text to achieve accurate results. After the webinar, you will be able to train your own NER models with your own data in Spark NLP.

Presented by Veysel Kocaman, Senior Data Scientist and ML Engineer at John Snow Labs

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State-of-the-art named entity recognition with BERT | Webinar

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