Projects in Awesome Lists tagged with model-interpretability
A curated list of projects in awesome lists tagged with model-interpretability .
https://github.com/kserve/kserve
Standardized Serverless ML Inference Platform on Kubernetes
artificial-intelligence genai hacktoberfest istio k8s knative kserve kubeflow kubernetes llm-inference machine-learning mlops model-interpretability model-serving pytorch service-mesh sklearn tensorflow xgboost
Last synced: 14 Mar 2026
https://github.com/kitops-ml/kitops
An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.
ai code datasets devops devops-tools gguf hacktoberfest kubernetes kubernetes-deployment ml mlops mlops-tools model-interpretability model-serving models opensource platform-engineering pytorch sklearn tensorflow
Last synced: 15 May 2025
https://github.com/kitops-ml/kitops?tab=readme-ov-file
An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.
ai code datasets devops devops-tools gguf hacktoberfest kubernetes kubernetes-deployment ml mlops mlops-tools model-interpretability model-serving models opensource platform-engineering pytorch sklearn tensorflow
Last synced: 28 Apr 2025
https://github.com/jozu-ai/kitops
An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.
ai code datasets devops devops-tools gguf hacktoberfest kubernetes kubernetes-deployment ml mlops mlops-tools model-interpretability model-serving models opensource platform-engineering pytorch sklearn tensorflow
Last synced: 16 Mar 2025
https://github.com/zphang/saliency_investigation
Code for "Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability" (https://arxiv.org/abs/2010.09750)
model-interpretability saliency-methods
Last synced: 13 Apr 2025
https://github.com/aimaster-dev/default_loan_prediction
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.
automation banking-applications classification credit-risk explainability finance fintech flask fraud-detection lightgbm loan-prediction loan-prediction-analysis model-interpretability roc-auc shap sklearn vuejs xgboost
Last synced: 01 May 2026
https://github.com/shuyib/chronic-kidney-disease-kaggle
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-cleaning-pipeline data-science data-transformation data-visualization diagnostics dimensionality-reduction feature-engineering feature-selection health-data-analysis health-data-science machine-learning machine-learning-algorithm machine-learning-algorithms model-interpretability preventative-medicine
Last synced: 19 Apr 2025
https://github.com/ondrejhruby/airbnb-analysis-machine-learning
A comprehensive end-to-end machine learning project analyzing Airbnb listings data. This project includes exploratory data analysis, model training, optimization, and model interpretability, using a randomly generated dataset for demonstration purposes.
airbnb-data data-science data-visualization exploratory-data-analysis hyperparameter-tuning machine-learning model-interpretability python regression-analysis
Last synced: 20 Jul 2025
https://github.com/shelton-beep/predicting-gpa-using-lifestyle-factors
Predicting student GPA using lifestyle factors like study habits, sleep, and stress levels. A machine learning model built to help students and educators understand the impact of lifestyle choices on academic performance.
data-analysis data-preprocessing data-science feature-engineering gpa-prediction machine-learning model-interpretability predictive-modeling python regression-analysis student-performance xgboost
Last synced: 04 May 2026
https://github.com/vinit714/player-retention-analysis
A complete Streamlit + Machine Learning + SHAP + NLP project to analyze, predict, and improve player retention in games. This project simulates a game environment, models churn behavior, and provides insights using SHAP, NLP word clouds, and strategy simulators.
churn-prediction classification data-visualization eda feature-engineering game-analytics game-data-analysis gaming-analytics machine-learning model-interpretability nlp pandas player-retention python retention-analysis sckiit-learn shap streamlit wordcloud
Last synced: 08 May 2026
https://github.com/shreyavijaykumar/pathmnist-xai-lightweight-explainable-cnn-for-medical-imaging
A lightweight Explainable AI CNN for PathMNIST medical imaging, achieving 91%+ accuracy with Integrated Gradients and SQLite-based attribution storage. Built in PyTorch, this scalable model delivers high performance, transparency, and real-world readiness, making it ideal for medical AI, edge deployment, and explainable deep learning research.
ai captum cnn computer-vision deep-learning edge-ai explainable-ai healthcare-ai integrated-gradients lightweight-model medical-ai medical-imaging ml-for-health model-interpretability open-source-ai pathmnist pathology pytorch scalable-ai sqlite
Last synced: 09 May 2026
https://github.com/mattjesc/federated-learning-simulation-1gpu-mi-is
Federated Learning Simulation on a Single GPU with Model Interpretability and Interactive Visualization
ai cuda deep-learning distributed-systems federated-learning gpu hpc keras machine-learning ml model-interpretability python pytorch simulation streamlit tensorflow
Last synced: 05 Jan 2026
https://github.com/mindful-ai-assistants/2-social-buzz-ai-gboost-and-lowdefault-modeling
2-Gradient Boosting Machines and Low-Default Modeling: A repository for research, implementation, and best practices with Gradient Boosting methods (GBM, XGBoost, LightGBM), H2O AutoML, and robust strategies for modeling extreme class imbalance ("Low Default") in data science for finance and risk.
anomaly-detection auto-machine-learning credit-risk disease-prediction financia-lmodeling fraud-detection gbm gradientboosting h2o imbalanced-data lightgbm low-default-modeling machinelearning model-interpretability natural-language-processing oneness-consciousness randomforest risk-analytics smote xgboost
Last synced: 09 Oct 2025
