Implement Named Entity Recognition with BERT

In this course, you'll learn about the state-of-the-art transformer technique called BERT, how to tag respective news domain entities to classify information, and how to get relevant insights about the geo-political news using deep learning library.

Classifying information into multiple domain entities is quite important for an enterprise to garner key insights. In this course, Implement Named Entity Recognition with BERT, you’ll gain the ability to tag referential entities based on domain text. First you’ll explore the key benefits of transformers. Next, you’ll discover the usage and advantages of named entity recognition. Finally, you’ll use PyTorch to tag entities based on domain data and BERT technique. When you’re finished with this course, you’ll have the skills and knowledge on how to implement named entity recognition with BERT and retrieve context about the text which leads to contextual tagging.

• Course Overview 1min
• Introducing Key Benefits of Transformers 4mins
• Analyzing Key Differentiators of BERT 10mins
• Leveraging Key Benefits of NER for Geopolitical Data 13mins
• Implementing BERT Based NER Using PyTorch 8mins