| Step | Fast | Description |
|---|---|---|
| caption_images | Predict image captions using pretrained DL models | |
| classify_text | Classify texts using any model from the Hugging Face hub | |
| clean_categories | Clean a given column of categories or lists of categories using OpenAI | |
| describe_clusters | Describe your clusters from their given relevant TF-IDF terms using OpenAI | |
| fetch_demographics_es | Fetch Spanish demographic census data given a geographical location in each row | |
| fetch_full_contact_domains | Enrich a dataset containing links (URLs) to companies’ online presence using the FullContact service | |
| fetch_full_contact_emails | Enrich a dataset containing email addresses with personal information using the FullContact service | |
| fetch_google_places | Fetch information about the most relevant places surrounding a location | |
| fetch_google_vision | Analyze images given their URL using the Google Vision API | |
| fetch_location | Extract formatted address, locality, area, state, country and geographical coordinates from one or more address columns | |
| fetch_openreview | Fetch publications submitted to one or more conferences via OpenReview | |
| fetch_social_shares | Fetch the number of times a Url was shared on Facebook | |
| fetch_twitter | Enriches a dataset containing tweets with information about their authors | |
| fetch_url_content | Fetch the main text from a web URL, and return its title, author, content, excerpt and domain | |
| infer_gender | Try to infer a person’s gender given a first name | |
| infer_language | Detect the language used for each text in the input column | |
| infer_missing | Train and use a machine learning model to predict (impute) the missing values in a column | |
| infer_missing_with_probs | Train and use a machine learning model to predict (impute) the missing values in a column | |
| infer_sentiment | Parse text and calculate the overall positive or negative sentiment polarity | |
| prompt_ai | Call OpenAI’s models on each row of the dataset for a given prompt | |
| zeroshot_classify_text | Classify texts using custom labels/categories |
Prepare
Enrich
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