rodrigobressan/entity_embeddings_categorical
Discover relevant information about categorical data with entity embeddings using Neural Networks (powered by Keras)
This tool helps data professionals understand and represent complex categorical data, like product IDs or customer segments, using neural networks. You provide a CSV file with your categorical data and a target variable, and it outputs numerical 'embeddings' that capture the hidden relationships within your categories. This is designed for data scientists or machine learning engineers who need to improve the performance of predictive models.
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Use this if you need to transform high-cardinality categorical variables into meaningful numerical representations for machine learning models, especially for regression or classification tasks.
Not ideal if you are looking for a no-code solution or if your primary goal is simple data cleaning rather than advanced feature engineering for predictive modeling.
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70
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Language
Python
License
MIT
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Last pushed
Dec 08, 2022
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