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model-interpretability

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rehmanzafar / xai-iml-sota

Star 72

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

machine-learning human-in-the-loop interpretability explainable-artificial-intelligence researchers interactive-machine-learning deep-learning-visualization human-in-the-loop-machine-learning explainable-ml xai interpretable interpretable-machine-learning iml model-interpretability explainable interpretable-models explainable-models interpretable-learning explaining-ai explanation-methods
  • Updated Sep 29, 2022
  • R

Ankit-Kumar-Saini / Coursera_TensorFlow_Advanced_Techniques_Specialization

Star 10

Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.

object-detection image-segmentation generative-adversarial-networks auto-encoders saliency-map mask-rcnn variational-autoencoders coursera-specialization retina-net model-interpretability tensorflow2 functional-api custom-model-development custom-loss-functions gradcam-visualization custom-layers gradient-tape-optimization custom-training-loops
  • Updated Jun 9, 2021
  • Jupyter Notebook

aimaster-dev / default_loan_prediction

Star 9

This project automates bank credit risk assessment using AI and machine learning models to predict loan defaults. It streamlines the credit process with predictive analytics, model evaluation, explainability (SHAP), and deployment readiness.

flask finance automation vuejs sklearn fintech xgboost classification lightgbm banking-applications fraud-detection roc-auc credit-risk loan-prediction-analysis shap explainability model-interpretability loan-prediction
  • Updated May 29, 2025
  • JavaScript

Shuyib / chronic-kidney-disease-kaggle

Star 8

Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.

data-science machine-learning machine-learning-algorithms data-transformation data-visualization feature-selection dimensionality-reduction feature-engineering diagnosis health-data-analysis machine-learning-algorithm explainable-ai model-interpretability data-cleaning-pipeline health-data-science preventative-medicine
  • Updated May 23, 2025
  • Jupyter Notebook

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