# Text AI resources

> Text AI resources - Provides links to Text AI resources available in DataRobot.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-04-24T16:03:56.607525+00:00` (UTC).

## Primary page

- [Text AI resources](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/textai-resources.html): Full documentation for this topic (HTML).

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [Modeling](https://docs.datarobot.com/en/docs/classic-ui/modeling/index.html): Linked from this page.
- [Specialized workflows](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/index.html): Linked from this page.
- [Automated transformations](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/model-ref.html#automated-feature-transformations): Linked from this page.
- [Clustering based on text collections](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/unsupervised/clustering.html): Linked from this page.
- [Aggregation and imputation in time series projects](https://docs.datarobot.com/en/docs/classic-ui/modeling/time/ts-modeling-data/ts-data-prep.html#set-manual-options): Linked from this page.
- [Composable ML transformers](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/cml/cml-blueprint-edit.html): Linked from this page.
- [Coefficients](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/describe/coefficients-classic.html): Linked from this page.
- [Text Mining](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/other/analyze-insights.html#text-mining): Linked from this page.
- [Text Explanations](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/predex-text.html): Linked from this page.
- [Multilabel modeling for text categorization](https://docs.datarobot.com/en/docs/classic-ui/modeling/special-workflows/multilabel-classic.html): Linked from this page.
- [Example: Capturing sentiment in text](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/cml-ref/cml-sentiment-example.html): Linked from this page.
- [NLP Fine-Tuner blueprints](https://docs.datarobot.com/en/docs/release/archive-release-notes/pre-10/v8.0/v8.0.0-aml.html#nlp-fine-tuner-blueprints-for-multi-modal-datasets-in-any-language): Linked from this page.
- [FastText for language detection](https://docs.datarobot.com/en/docs/release/cloud-history/2022-announce/july2022-announce.html#nlp-autopilot-with-better-language-support-now-ga): Linked from this page.
- [TinyBERT featurizer](https://docs.datarobot.com/en/docs/release/archive-release-notes/pre-10/v7.1/v7.1.0-aml.html#tiny-bert-pre-trained-featurizer-implementation-extends-nlp): Linked from this page.

## Documentation content

# Text AI resources

Text AI in DataRobot allows you to seamlessly incorporate text data into your model without being a Natural Language Processing (NLP) expert and without injecting extra steps in the model building process. With models and preprocessing steps designed specifically for NLP, DataRobot supports all languages from [ISO 639](https://en.wikipedia.org/wiki/List_of_ISO_639-2_codes), the set of standards for representing names for languages and language groups.

The tools available for working with text are described in the following sections.

| Topic | Description |
| --- | --- |
| Working with text |  |
| Automated transformations | Learn about automated feature engineering for text, built to enhance model accuracy. |
| Clustering based on text collections | Use clustering for detecting topics, types, taxonomies, and languages in a text collection. |
| Aggregation and imputation in time series projects | Set handling for text features in time series projects. |
| Composable ML transformers | Edit model blueprints, including pre-trained transformers, to best represent text features. |
| Model insights |  |
| Coefficients | See how text-preprocessing transforms text found in a dataset into a form that can be used by a DataRobot model. |
| Text Mining | Display the most relevant words and short phrases in any variables detected as text. |
| Word cloud | Display the most relevant words and short phrases found in your dataset in word cloud format. |
| Text Explanations | Visualize not only the text feature that is impactful, but also which specific words within a feature are impactful. |
| Multilabel modeling for text categorization | Use multilabel classification for text categorization. |
| Example: Capturing sentiment in text | See an example of uplifting a model by capturing sentiment in the text. |
| Text-related feature announcements |  |
| NLP Fine-Tuner blueprints | Read about NLP Fine-Tuner blueprints. |
| FastText for language detection | Read about FastText for language detection at data ingest. |
| TinyBERT featurizer | Read about using Google's Bidirectional Encoder Representations from Transformers (distilled version). |