Named Entity Recognition (NER) Tutorials in TensorFlow NLP

Named Entity Recognition (NER) is a key task in Natural Language Processing (NLP), which aims to identify and classify named entities in text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.

Here are some tutorials that guide you through the process of performing NER using TensorFlow NLP:

• Getting Started with TensorFlow NLP
• Using TensorFlow NLP for NER

Tutorials

1. Understanding NER in TensorFlow NLP
2. Building a Basic NER Model with TensorFlow NLP
3. Advanced Techniques in NER with TensorFlow NLP

Resources

• TensorFlow NLP Documentation
• GitHub Repository for TensorFlow NLP

Sample Image

Here's an example of a NER model in action: