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Implementing and Interpreting a Deep Learning Model for Fairness using SHAP

Description

This project focuses on implementing a deep learning model to predict income levels using the UCI Adult Dataset. It utilizes SHAP for explaining model predictions and assessing fairness, while also addressing potential biases through class re-weighting. The project highlights key techniques in model transparency and ethical AI.

Utilities Used

  • Python
  • Google Colab
  • TensorFlow
  • scikit-learn
  • pandas
  • SHAP

Project Walk-through

Data Loading & Preprocessing


Model Building & Training


Interpretability with SHAP


Bias Detection & Mitigation


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Topics

explainable-ai shap model-interpretability fairness-in-ml

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