The most powerful aspect of MonkeyLearn is really in the ability of users to create custom modules for their own processes. 🚀
When a custom module for text analysis works well it often marks the difference between a drawn out, tedious process and one where all the answers magically appear.
Custom modules do need to be built from scratch, however, and this requires a good amount of investment from a user to define, build, and train.
This guide will help get you started on how to build custom modules that can automatically classify text so that you and your team can take actions more quickly.
This process is divided 5 major steps as follows:
- Defining a category tree
- Data Gathering
- Data Tagging
- Training the Classifier
- Testing & Improving the Classifier
For a full guide on the subject, please see our blog post on How to Create Custom Classifiers with Machine Learning.