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Dense neural network that predicts animal adoption rates, w/ accuracy up to 87%

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yuhanx0728/pet-adoption-ml-model

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Project description

I built and trained a dense neural network(in train_v3.ipynb) on 15K animal profiles, each with 23 features, to predict adoption speed with an accuracy of 86%. We hope this model can help shelters improve pet profiles for faster adoptions and provide a numeric evaluation while developing online profiles for pets.

This is part of the final project for the class AI for Social Good in CMU.

Tech stack

Pytorch

Additional resources on this project

A paper I wrote with my team as part of this project

A poster I made with my team as part of this project - we won the most popular award during poster session

A presentation I had done with my team as part of this project

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Dense neural network that predicts animal adoption rates, w/ accuracy up to 87%

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