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Projects in Awesome Lists tagged with model-interpretability

A curated list of projects in awesome lists tagged with model-interpretability .

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/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/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: 24 Mar 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/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

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: 28 Jun 2025

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/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: 16 Sep 2025