Search Enhancement Using Natural Language Processing
Natural Language Processing (NLP) helps computers gain a deeper understanding of human language by adding context and structure. With NLP, your search solution can return better results because it can better interpret what you’re asking it to find (searches for "big data lake" shouldn't return Lake Tahoe). This instructor-led course will teach you how to integrate and use NLP in your search applications. After exploring Part-of-Speech (POS) tagging, Named Entities Recognition (NER), and the Openlp ingest pipeline, you will learn how to design and configure your applications to support those features and build better search in your own use case. After completing this course, you will be able to use NLP to improve the relevancy of your search engine.
- Overview of Natural Language Processing
- The NLTK Python library
- Part-of-Speech (POS) Tagging and Entity Recognition
- The Openlp Ingest Pipeline
- Enhancing Searching with NLP
This course is a module of the Data Science specialization. Find out how our focused Training Specializations can help you with your use case.
Data Scientists, Data Architects, Data Engineers, Software Developers
Virtual Classroom - 1 Day | 2-3 hours
- We recommend you have taken Elasticsearch Engineer I and Elasticsearch Engineer II or possess equivalent knowledge. Engineer I and Engineer II teach the concepts that are the foundation upon which all specializations are built.
- Knowledge of Python programming and NLP is recommended
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (Safari is not 100% supported)