Text Classification with Elasticsearch
Text analysis, tokenization, and stop word removal is as much a function of search as it is of classification, making Elasticsearch the perfect tool for text classification. This course will teach you how to build a classification system using the same features that make Elasticsearch so powerful for search.
Note: This course is a module of the Data Science specialization.
After exploring precision, recall, F1 scoring, fallback mechanisms and more, you will learn how to use tools like percolation and significant terms aggregation to build better text classification systems in your own use case.
- Designing Classification Systems with the Elastic Stack
- Query Optimization with Significant Terms Aggregations
- Using Percolators for Classification
- Fallback Planning
Data Scientists, Data Architects, Data Engineers, Software Developers
- 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.
- Familiarity with Python and basic statistics
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (Safari is not 100% supported)
This course is a module of the Data Science specialization. Find out how our focused Training Specializations can help you with your use case.
General Training Information