georgian-io/Multimodal-Toolkit

Multimodal model for text and tabular data with HuggingFace transformers as building block for text data

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This toolkit helps data scientists and machine learning engineers build predictive models that combine insights from both text descriptions and structured data, like numbers or categories. You feed in datasets containing customer reviews, product details, or property listings, alongside numerical features like prices or ratings, and categorical data such as product type or location. The output is a more accurate classification or regression model, for tasks like predicting customer recommendations or property prices.

618 stars. No commits in the last 6 months.

Use this if you need to build advanced classification or regression models where both rich text data and traditional numerical/categorical data are available and crucial for making accurate predictions.

Not ideal if your problem solely involves text analysis or only uses tabular data, as it's designed specifically for combining both data types.

predictive-modeling text-analytics data-science e-commerce real-estate-analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

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Stars

618

Forks

92

Language

Python

License

Apache-2.0

Last pushed

Oct 30, 2024

Commits (30d)

0

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