In this liveProject you’ll develop a chatbot that can extract entities from user messages using the Hugging Face NLP library. Entity extraction pulls relevant data from chunks of text. Your challenges will include building a Named Entity Recognition task with the BERT transformer, and fine-tuning it to a medical context. You’ll then integrate your tasks into a chatbot.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This liveProject is for intermediate Python programmers with some experience in natural language processing. To begin this liveProject you will need to be familiar with:
- Intermediate Python
- Basics of Jupyter Notebook
- Basics of natural language processing
you will learn
In this liveProject, you’ll learn to use the powerful Hugging Face Transformers library to create chatbots using the Named Entity Recognition (NER) natural Language Processing (NLP) task.
- Build a NER NLP pipeline with a BERT transformer
- Create NER NLP pipeline fine-tuned to a medication context
- Integrate NER pipeline into a chatbot
- Integrate medication NER pipeline into a chatbot