In the digital era where the majority of information is made up of text-based data, text mining plays an important role for extracting useful information, providing patterns and insight from an otherwise unstructured data. In this workshop, you'll learn how to train your own, customized named entity recognition model. You’ll find out how to apply it to extract entities from text, and create entity relation networks.
Furthermore, we’ll look at how to preprocess and transform textual data into numbers to feed them into deep neural networks (LSTM) for prediction.
This workshop is run by Julian Bunzel & Andisa Dewi (KNIME).
We're keeping the KNIME Community connected throughout April and May by bringing you a series of online events. Find more here:
More online workshops
|May 5||Behind the Scenes of Machine Learning|
|May 7||Building a Drug Discovery Workflow in 8+1 steps with KNIME|
|May 12||Deep Learning for Image Analysis|
|May 14||KNIME Big Data Workshop|
|May 19||GDPR Compliance through Advanced Anonymization Techniques|
You’ll receive a zoom link with your registration confirmation. Make sure you have a stable internet connection!
Yes, we will have a Q&A and we'll do our best to answer these at the end of the workshop.
Download the latest free, open source version of knime here: knime.com/download