Creating Named Entity Recognition Systems with Python

This course shows how data professionals and software developers make use of the Python language in order to create Named Entity Recognition (NER) systems by leveraging the language’s powerful set of open-source NLP libraries.

In this course, Creating Named Entity Recognition Systems with Python, you'll look at how data professionals and software developers make use of the Python language. First, you'll explore the unique ability of such systems to perform information retrieval by identifying specific classes of entities in texts. Next, you'll learn how to install prerequisite tools and how to create in a step-by-step manner all the specific components of performant NER systems. Finally, you'll be able to create Named Entity Recognition (NER) systems by leveraging the language’s powerful set of open-source NLP libraries. When you’re finished with this course, you’ll have the skills and knowledge of creating named entity recognition systems with Python

• Course Overview 2mins
• Getting Started 17mins
• Preprocessing Data for NER Training 9mins
• Building Linear Classifiers for NER Systems 13mins
• Building Conditional Random Fields (CRFs) 37mins
• Comparing Custom NER Models to spaCy’s NER 13mins