- Getting Started
- Administration
- Manage Sources and Datasets
- Understanding the data structure and permissions
- Create a data source in the GUI
- Uploading a CSV file into a source
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend a dataset's settings
- Delete messages via the UI
- Delete a dataset
- Export a dataset
- Using Exchange Integrations
- Preparing Data for .CSV Upload
- Model Training and Maintenance
- Understanding labels, entities and metadata
- Label hierarchy and best practice
- Defining your taxonomy objectives
- Analytics vs. automation use cases
- Turning your objectives into labels
- Building your taxonomy structure
- Taxonomy design best practice
- Importing your taxonomy
- Overview of the model training process
- Generative Annotation (NEW)
- Understanding the status of your dataset
- Model training and labelling best practice
- Training with label sentiment analysis enabled
- Train
- Introduction to 'Refine'
- Precision and recall explained
- Precision and recall
- How does Validation work?
- Understanding and improving model performance
- Why might a label have low average precision?
- Training using 'Check label' and 'Missed label'
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using 'Rebalance'
- When to stop training your model
- Using Analytics & Monitoring
- Automations and Communications Mining
- FAQs and More
Deprecated Models
User permissions required: Tenant Admin.
The Deprecated Models page shows you any model versions for datasets in your tenant that will soon be deprecated. All the production datasets are using more recent, improved model versions.
Having an empty page is expected, because it means that no model is going to be deprecated soon.
To ensure optimal functionality and security, older pinned model versions (which will be at least 12 months old) may be scheduled for deprecation.
To ensure a smooth transition, all deprecated models are flagged well in advance. You can find early deprecation indicators both within this page and in the Models page of the relevant dataset. This proactive approach gives you sufficient time to adjust your work without disruption.
Following the initial announcement, you have a transition period of no less than three months. After this period ends, deprecated versions will be deemed unsupported. Consequently, unsupported versions will not be accessible via the API.
You have to unpin deprecated model versions after pinning a more recent model version within the same dataset. This ensures the smooth continuation of service and API calls during the transition.
