Creating a Custom Vocabulary for NLP tasks
For NLP tasks, the first step is to pre-process text for training. Let’s say you have the English language model ,you will have a model that includes over 1 million items of vocab, many classes of entity recognition and a lot of compound noun recognition. But what happens when we need to add new terms and customize the vocabulary? In this talk, we show an approach on how to create a custom vocabulary that can be further used for any NLP tasks.
Senior Data Scientist at Boomi
Swagata is a Data Professional with over 6 years experience in Healthcare, Retail and Platform Integration industry. She is an avid blogger and writes about state of the art developments in the AI space. In her spare time, she loves to play her guitar, sip masala chai and find new spots for doing Yoga. Connect with her here – https://www.linkedin.com/in/swagata-ashwani/