Projects in Awesome Lists tagged with shap
A curated list of projects in awesome lists tagged with shap .
https://github.com/shap/shap
A game theoretic approach to explain the output of any machine learning model.
deep-learning explainability gradient-boosting interpretability machine-learning shap shapley
Last synced: 11 Dec 2025
https://github.com/maif/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
ethical-artificial-intelligence explainability explainable-ml interpretability lime machine-learning python shap transparency
Last synced: 30 Jan 2026
https://github.com/MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
ethical-artificial-intelligence explainability explainable-ml interpretability lime machine-learning python shap transparency
Last synced: 26 Mar 2025
https://github.com/oegedijk/explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
dash dashboard data-scientists explainer inner-workings interactive-dashboards interactive-plots model-predictions permutation-importances plotly shap shap-values xai xai-library
Last synced: 29 Jan 2026
https://github.com/linkedin/fasttreeshap
Fast SHAP value computation for interpreting tree-based models
explainable-ai interpretability lightgbm machine-learning random-forest shap xgboost
Last synced: 17 Aug 2025
https://github.com/linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
explainable-ai interpretability lightgbm machine-learning random-forest shap xgboost
Last synced: 19 Jul 2025
https://github.com/predict-idlab/powershap
A power-full Shapley feature selection method.
data-science feature-selection machine-learning shap
Last synced: 07 Jul 2025
https://github.com/feedzai/timeshap
TimeSHAP explains Recurrent Neural Network predictions.
explainability rnn shap shapley-values
Last synced: 05 Apr 2025
https://github.com/tvdboom/atom
Automated Tool for Optimized Modelling
automl dagshub data-exploration data-pipeline data-science interactive-visualizations machine-learning mlflow model-predictions modelling python scikit-learn shap visualization
Last synced: 06 Apr 2025
https://github.com/ing-bank/probatus
SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.
binary-classifiers data-analysis data-science feature-elimination machine-learning multi-class-classification recursive-feature-elimination regressors shap statistics tree-model
Last synced: 07 Apr 2025
https://github.com/astrazeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
artificial-intelligence data-science deep-learning explainability explainable explainable-ai explainable-artificial-intelligence explainable-ml lime machine-learning owen-value shap shapley shapley-additive-explanations shapley-decomposition shapley-q-value shapley-value xai
Last synced: 26 Dec 2025
https://github.com/ModelOriented/survex
Explainable Machine Learning in Survival Analysis
biostatistics brier-scores censored-data cox-model cox-regression explainable-ai explainable-machine-learning explainable-ml explanatory-model-analysis interpretable-machine-learning interpretable-ml machine-learning probabilistic-machine-learning r r-package shap survival-analysis time-to-event variable-importance xai
Last synced: 05 May 2025
https://github.com/nredell/shapml.jl
A Julia package for interpretable machine learning with stochastic Shapley values
feature-importance iml interpretable-machine-learning julia shap shapley shapley-value stochastic-shapley-values
Last synced: 10 Apr 2025
https://github.com/snehankekre/streamlit-shap
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
explainability interpretability machine-learning shap shapley streamlit streamlit-component
Last synced: 21 Aug 2025
https://github.com/nredell/shapflex
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
causal-inference causal-networks causality ensemble feature-importance iml interpretable-machine-learning machine-learning package r r-package shap shapley shapley-value shapley-values
Last synced: 13 Apr 2025
https://github.com/nredell/shapFlex
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
causal-inference causal-networks causality ensemble feature-importance iml interpretable-machine-learning machine-learning package r r-package shap shapley shapley-value shapley-values
Last synced: 17 Sep 2025
https://github.com/xplainable/xplainable
Real-time explainable machine learning for business optimisation
auto-ml data-analytics data-science explainable-ai explainable-ml machine-learning machine-learning-algorithms prediction predictions python shap statistics xai xplainable
Last synced: 17 May 2026
https://github.com/AidanCooper/shap-analysis-guide
How to Interpret SHAP Analyses: A Non-Technical Guide
data-science machine-learning shap tutorial
Last synced: 01 May 2025
https://github.com/marvinbuss/explainableml-vision
This repository introduces different Explainable AI approaches and demonstrates how they can be implemented with PyTorch and torchvision. Used approaches are Class Activation Mappings, LIMA and SHapley Additive exPlanations.
cam class-activation-maps data-science explainable-ai explainable-deepneuralnetwork explainable-ml hymenoptera-dataset lime machine-learning notebook pytorch shap transfer-learning
Last synced: 29 Jul 2025
https://github.com/cloudera/cml_amp_explainability_lime_shap
Learn how to explain ML models using LIME and SHAP.
explainability interpretability lime shap
Last synced: 13 Apr 2025
https://github.com/haghish/shapley
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
class-imbalance class-imbalance-problem feature-extraction feature-importance feature-selection machine-learning machine-learning-algorithms shap shap-analysis shap-values shapely shapley-additive-explanations shapley-decomposition shapley-value shapley-values shapleyvalue weighted-shap weighted-shap-confidence-interval weighted-shapley weighted-shapley-ci
Last synced: 21 Feb 2026
https://github.com/sunnynguyen-ai/fraud-detection-system
Real-time fraud detection system using ensemble ML models, featuring streaming data processing, explainable AI with SHAP, and production-ready deployment with FastAPI and Docker.
data-science docker ensemble-models fastapi feature-engineering fraud-detection machine-learning mlops production-ml python random-forest real-time-ml shap streamlit xgboost
Last synced: 04 May 2026
https://github.com/hi-paris/xper
A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
explainability interpretability machine-learning performance-metrics shap shapley-value
Last synced: 09 Apr 2026
https://github.com/rodrigobressan/keras_boston_housing_price
Keras 101: A simple Neural Network for House Pricing regression
boston-housing-price-prediction jupyter-notebook keras model-explanation shap
Last synced: 07 Apr 2025
https://github.com/akthammomani/Menara-App-Predict-House-Price-CA
Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area
aws-ec2 deep-learning eli5 haversine-distance haversine-formula lime machine-learning neural-network python shap sklearn streamlit supervised-learning time-series unsupervised-learning
Last synced: 10 May 2025
https://github.com/basics-lab/spectral-explain
Fast XAI with interactions at large scale. SPEX can help you understand the output of your LLM, even if you have a long context!
explainability explainable-ai llm-interpretability shap sparse-transformer xai
Last synced: 17 Mar 2026
https://github.com/hiroki-kawauchi/SHAPObjectDetection
SHAP-Based Interpretable Object Detection Method for Satellite Imagery
interpretability object-detection pytorch satellite-imagery shap
Last synced: 25 Sep 2026
https://github.com/chaitjo/working-women
Code for the paper 'Working Women and Caste in India' (ICLR 2019 AI for Social Good Workshop)
caste gradient-boosting india interpretability machine-learning shap social-good women
Last synced: 14 Mar 2025
https://github.com/harshjuly12/enhancing-explainability-in-fake-news-detection-a-shap-based-approach-for-bidirectional-lstm-models
Enhancing Explainability in Fake News Detection uses SHAP and BiLSTM models to improve the transparency and interpretability of detecting fake news, providing insights into the model's decision-making process.
bidirectional-lstm lstm-neural-networks shap xai
Last synced: 04 Sep 2025
https://github.com/ata-turhan/titanic-survival-prediction
A comprehensive solution for the Kaggle Titanic Challenge, featuring advanced data exploration, feature engineering, model training, and explainable AI techniques. Includes Logistic Regression, RandomForest, XGBoost, and Stacked Ensembles with SHAP and permutation importance for model interpretability.
classification kaggle python shap xgboost
Last synced: 09 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/laminetourelab/explainable-ai
In this repository you will fine explainability of machine learning models.
explainability explainable-ai explainable-ml explainerdashboard interpretability lime machine-learning model shap shapash shapely shapley shapley-additive-explanations
Last synced: 25 Jan 2026
https://github.com/mayurdivate/deepcancersignatures
This repository contains code used to build and interpret a deep learning model. It is a DNN classifier trained using gene expression data (TCGA). Then is interpreted to identify cancer specific gene expression signatures.
Last synced: 28 Oct 2025
https://github.com/tsitsimis/tinyshap
Python package providing a minimal implementation of the SHAP algorithm using the Kernel method
explainable-ai machine-learning ml python-package shap shapely xai
Last synced: 14 Jan 2026
https://github.com/abhaysingh71/ai-powered-healthcare-intelligence-network
The AI-Powered Healthcare Intelligence Network is an AI-driven system offering disease prediction, drug recommendations, heart disease risk assessment, and an AI medical chatbot. Using ML, NLP, and LLMs, it provides accurate diagnoses, insights, and recommendations, enhancing healthcare accessibility, efficiency, and decision-making .
airtificialintelligence chatbot data-analysis data-science datawrangling disease-prediction healthcare-ai heart-disease huggingface langchain large-language-models lightgbm machine-learning mistral-7b recommendation-system retrieval-augmented-generation sentence-transformers shap vector-database
Last synced: 01 Feb 2026
https://github.com/miolab/jupyterlab_poetry
JupyterLab runtime environment with Poetry and Docker management.
docker jupyterlab nltk poetry python3 pytorch scikit-learn scipy shap xgboost
Last synced: 26 Oct 2025
https://github.com/selasie5/explainable-backend
A Fast API Backend Engine for explainable- Turn raw datasets and machine learning models into human-understandable visual stories
artificial-intelligence docker docker-compose fastapi matplotlib python shap uvicorn
Last synced: 29 Jul 2026
https://github.com/hbaniecki/compress-then-explain
Efficient and accurate explanation estimation with distribution compression (ICLR 2025 Spotlight)
dalex explainable-ai feature-attribution goodpoints interpretable-machine-learning kernel-thinning pdp sage shap
Last synced: 11 Apr 2025
https://github.com/urme-b/calmsense
Logistic regression, random forest, XGBoost, LightGBM and a 1D-CNN on wearable physiology; subject-independent LOSO, SHAP explainability, in-browser React demo
lightgbm onnx pytorch react scikit-learn shap xgboost
Last synced: 16 Jul 2026
https://github.com/jpmorganchase/cf-shap
Counterfactual SHAP: a framework for counterfactual feature importance
algorithmic-recourse counterfactual-explanations counterfactuals explainability explainable-ai explainable-artificial-intelligence explainable-machine-learning explainable-ml explanations facct2022 feature-attribution feature-importance machine-learning shap shapley shapley-values tree-based xgboost
Last synced: 23 Aug 2025
https://github.com/ab93/shap-monitor
Monitor and explain your ML model in production
explainable-ai interpretability shap xai
Last synced: 18 Apr 2026
https://github.com/pyladiesams/ai-in-finance-python-lecture-beginner-may2022
AI in Finance - Python interactive lecture for students studying Finance
ai beginner-friendly creditcard finance interpretable-machine-learning machine-learning shap
Last synced: 07 May 2025
https://github.com/pavankethavath/microsoft-classifying-cybersecurity-incidents-with-ml
A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn
classificationreport correlation-analysis dataanalysis decision-tree-classifier exploratory-data-analysis feature-engineering feature-selection gradientboosting hyperparameter-tuning joblib lgbmclassifier logistic-regression machine-learning modelselection pandas randomforestclassifier randomsearchcv shap smote xgboost-classifier
Last synced: 23 Apr 2025
https://github.com/tommartensen/tic
TIC is a library that acts as a Toolbox for Interpretability Comparison.
complexity-faithfulness-graph interpretability lime shap
Last synced: 21 Sep 2025
https://github.com/josedv82/nba_schedule_xgboost_classifier
Predicting NBA game outcomes using schedule related information. This is an example of supervised learning where a xgboost model was trained with 20 seasons worth of NBA games and uses SHAP values for model explainability.
h2o h2oai nba-analytics nba-stats shap shapley-additive-explanations shapley-value supervised-learning xgboost xgboost-algorithm
Last synced: 29 Mar 2025
https://github.com/ksharma67/heart-failure-prediction
This problem is a typical Classification Machine Learning task. Building various classifiers by using the following Machine Learning models: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), XGBoost (XGB), Light GBM and Support Vector Machines with RBF kernel.
auc-roc-curve auc-roc-score decision-trees eda eli5 gridsearchcv lightgbm lime logistic-regression numpy pandas python random-forest seaborn shap skit-learn sklearn svm xgboost
Last synced: 08 Apr 2026
https://github.com/miltiadiss/ceid_ne577-5g-architectures-technologies-applications-and-key-performance-indexes
This project involves predicting the downlink bitrate of mobile devices in 5G networks using machine learning (XGBoost Regressor) and deep learning (LSTM model). It includes data preprocessing, training and evaluation of the models, applying explainable AI (XAI) techniques such as SHAP, and optimizing feature selection based on XAI insights.
deep-learning explainable-ai lstm-neural-network shap xgboost-regression
Last synced: 17 Jun 2025
https://github.com/ksharma67/partial-dependent-plots-individual-conditional-expectation-plots-with-shap
The goal of SHAP is to explain the prediction of an instance x by computing the contribution of each feature to the prediction. The SHAP explanation method computes Shapley values from coalitional game theory. The feature values of a data instance act as players in a coalition.
eda individual-conditional-expectation matplotlib numpy pandas partial-dependence-plot python seaborn shap shapley-additive-explanations sklearn xgboost
Last synced: 11 Apr 2026
https://github.com/musadiqpasha/turkish-hate-speech-classification-explanation
Classify, explain, and rewrite Turkish hate speech tweets using BERT, SHAP, and LLaMA with PEFT fine-tuning.
bert-model explainability hate-speech-detection nlp peft-fine-tuning-llm shap transformers
Last synced: 12 Aug 2025
https://github.com/mayer79/lightshap
Lightweight Python implementation of SHAP
explainability interpretability ml shap shapley xai
Last synced: 09 Oct 2025
https://github.com/spags093/spotify_song_data
Part 1: Analysis of Spotify song data that uses Machine Learning to determine what features make a "hit" song on Spotify.
machine-learning matplotlib music pandas python scikit-learn seaborn shap spotify spotify-api tensorflow
Last synced: 02 Apr 2025
https://github.com/youhuipang/fx-risk-forecasting-system
An intuitive end-to-end web-app system that forecasts FX risk over the next 3 days, powered by explainable AI and real market data.
dashboard explainable-ai finance flask machine-learning prediction prediction-model risk-analysis risk-forecasting risk-modelling shap xgboost
Last synced: 02 Mar 2026
https://github.com/tedoaba/house-price-prediction-app
House-Price-Prediction-App
correlation feature-importance house-price-prediction numpy pandas python3 random-forest-regression seaborn shap skl streamlit
Last synced: 02 Apr 2026
https://github.com/ihuzaifashoukat/student-performance-analysis
Professional Data Science project analyzing student performance factors using XGBoost, SHAP implementation, and K-Means Clustering for student segmentation.
analytics clustering data-science education machine-learning python shap student-performance visualization xgboost
Last synced: 04 Apr 2026
https://github.com/zsxkib/most-under-and-over-priced-cars
Determine what influences and drives car prices given technical specs and identify which car(s) are the most under/overpriced and why.
analysis cars-dataset explainable-artificial-intelligence interpretable-machine-learning outlier-detection shap xgboost-regression
Last synced: 05 Apr 2025
https://github.com/rhenkin/rforceplots
Wrapper for shapjs node package for easy force plots in R without Python dependencies
data-science models r-package shap visualization
Last synced: 18 Jun 2025
https://github.com/ph-7/glm-with-sklearn-joblib-and-shap-project
GLM with sklearn, joblib and SHAP project
data-science glm joblib shap shap-analysis sklearn
Last synced: 18 May 2026
https://github.com/zeke320/xai-ric-book
リックテレコム出版「XAI（説明可能なAI）──そのとき人工知能はどう考えたのか？」の勉強用リポジトリ
ai book explainable-ai explainer python shap xai
Last synced: 20 Apr 2026
https://github.com/mbtiongson1/fuel-abemis
Project done in collaboration with BAFE Engineer Rosas in modelling fuel consumption in L/h of agricultural machinery like Tractors, Combiner Harvesters, etc. and interpreting the model using SHAP and LIME. Results show a significant improvement of 30% over linear regression model (OLS), with a +-0.95 L/h error (MSE).
agriculture lime machine-learning random-forest regression shap
Last synced: 06 Jul 2026
https://github.com/aqib121201/fairnlp-shap-based-bias-detection-in-multilingual-bert-models
Bias analysis in multilingual BERT using SHAP and fairness metrics (EN, DE, HI)
bias-detection fairness multilingual-bert nlp responsible-ai sentiment-analysis shap transformers
Last synced: 10 Aug 2025
https://github.com/kwokhing/shap-xai-demo
Demo on performing Explainable AI using the SHAP Library
explainable-ai explainable-ml shap xai
Last synced: 12 Aug 2025
https://github.com/cuonghoangit/geomineralinsight
This project uses machine learning to analyze geological, geochemical, aeromagnetic, and remote sensing data over 39,000 sq. km in southern India. It identifies high-probability zones for concealed Au, Cu, and PGE deposits using XGBoost, SHAP, and GeoPandas. Key features include automated pipelines, explainable AI, and GIS-ready maps.
data-pipelines explainable-ai feature-engineering geopandas geoscience geospatial-analysis gis hackathon-project machine-learning mineral-exploration python rasterio remote-sensing shap
Last synced: 04 Oct 2025
https://github.com/raju-2003/indiaai-cyberguard-ai-hackathon
An NLP-powered system to simplify cybercrime reporting by analyzing descriptions, categorizing incidents, and providing actionable insights.
matplotlib nltk numpy pandas python random-forest-classifier re scikit-learn seaborn shap spacy wordcloud
Last synced: 11 Apr 2026
https://github.com/priboy313/pandasflow
A set of custom python modules for friendly workflow on pandas
catboost data-analysis data-science pandas phik python scikit-learn shap
Last synced: 20 Jan 2026
https://github.com/benjikazzooe/diabetes_vorhersage
Machine Learning Model zur Diabetes-Klassifikation mit SHAP-Analyse
data-science explainable-ai machine-learning shap xgboost
Last synced: 20 Jan 2026
https://github.com/anondo1969/shamsul
Repository for the journal article 'SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction'
chest-x-ray clinical-decision-support-system deep-learning grad-cam heatmap-visualization human-annotation interpretability-methods lime lrp medical-significance quantitative-analysis shap
Last synced: 12 Jun 2025
https://github.com/suryadipbera1256/epileptic-seizure-recognition
Machine learning techniques are increasingly applied in the classification of drugs based on biomarkers related to epileptic seizures. Various studies highlight the use of deep learning and other machine learning models to enhance seizure detection and classification from EEG data.
confusion-matrix matplotlib seaborn shap svc-model
Last synced: 15 Jul 2026
https://github.com/prantikmedhi/nasa-koi-classification
ML pipeline classifying Kepler Objects of Interest into confirmed exoplanets, candidates, and false positives. XGBoost model, 94.2% accuracy, 0.922 macro F1, with SHAP explainability and full feature engineering pipeline on NASA's cumulative KOI table.
astronomy astrophysics classification data-science exoplanet-detection feature-engineering jupyter-notebook kepler-mission machine-learning nasa-exoplanet-archive python scikit-learn shap xgboost
Last synced: 15 Jul 2026
https://github.com/muneeb706/patient-no-show
Patient No Show Predictive Modeling Using RIPPER and Hoeffding Trees Algorithms
binary-classification hoeffding-trees interpretable-machine-learning predictive-modeling ripper shap
Last synced: 26 Mar 2025
https://github.com/silvano315/stroke_prediction
Stroke prediction with machine learning and SHAP algorithm using Kaggle dataset
classification eda explainability machine-learning shap stroke
Last synced: 20 Jul 2026
https://github.com/tszon/end-to-end_ds_ml_project
I built an end-to-end customer churn segregation and prediction project.
containerisation data-science docker explianable-ai exploratory-data-analysis feature-engineering hdbscan-clustering kmeans-clustering machine-learning mlflow preprocessing-data scikit-learn shap statistical-test statistical-tests streamlit supervised-learning visualisation vscode
Last synced: 16 Apr 2026
https://github.com/omidghadami95/efficientnetv2_catvsdog
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
binary binary-classification catvsdog catvsdog-classifier deep-learning efficientnet efficientnetv2 efficientnetv2-b0 explainable-ai explainable-ml fairness-ai fairness-ml gridsearch imbalanced-data imbalanced-dataset keras shap tensorflow2
Last synced: 17 Apr 2026
https://github.com/designer-coderajay/bfsi-credit-intelligence
Agentic AI loan underwriting platform for Indian BFSI sector. LangGraph v0.3 + 5 MCP servers (Bureau, GST, KYC, RBI Compliance, Account Aggregator) + XGBoost + SHAP + Kafka. RBI/DPDP 2023 compliant. Deployed on AWS Mumbai (ap-south-1).
agentic-ai bfsi fastapi fintech kafka langgraph loan-underwriting mcp mlflow mlops ocr python rbi-compliance shap xgboost
Last synced: 04 Jun 2026
https://github.com/hrolive/introduction-to-explainable-deep-learning-on-supercomputers
A solid foundational understanding of XAI, primarily emphasizing how XAI methodologies can expose latent biases in datasets and reveal valuable insights.
attention attention-maps convolutional-neural-networks deep-learning explainable-ai lime machine-learning permutation-importance python shap transformer visual-transformers
Last synced: 14 May 2026
https://github.com/k-ashik/genescout-ai-genetic-disease-pathologist
GeneScout: An interpretable AI Pathologist that predicts 5 genetic diseases with 93.5% accuracy using an Ensemble Voting Classifier and SHAP for clinical explainability.
data-science explainable-ai healthcare-ai machine-learning precision-medicine python scikit-learn shap streamlit
Last synced: 20 Apr 2026
https://github.com/oldhero5/talent_track
TalentTrack is an open‐source recruitment analytics web application built with Flask and Python. It leverages advanced machine learning techniques—such as Product Quantization (PQ) for candidate ranking and SHAP for model interpretability—to help HR teams and recruitment professionals identify high-quality candidates efficiently.
active-learning analytics candidate-ranking data-visualization faiss flask hrtech machine-learning open-source python recruitment shap talent-analytics
Last synced: 07 May 2026
https://github.com/speckledjim2/py_lucidum
Local-first browser workbench for exploring CSV and Parquet datasets with DuckDB, profiling, charts, UK maps, and optional GLM/GBM modelling.
browser-workbench csv data-profiling data-visualization duckdb exploratory-data-analysis fastapi gbm glm lightgbm local-first parquet python shap uk-postcodes
Last synced: 02 Aug 2026
https://github.com/mohammadi-hadi/explainable-sexism-detection
Transparent pipeline for online sexism detection combining explainable AI, feature selection, and ensemble learning (Applied Sciences, 2024)
ensemble-learning explainable-ai nlp sexism-detection shap text-classification
Last synced: 17 Aug 2026
https://github.com/mowne67/pyinterpret
A unified Python library for machine learning model interpretation (SHAP, LIME, permutation importance, partial dependence)
explainability feature-importance interpretability lime machine-learning model-explanation python scikit-learn shap xai
Last synced: 14 Sep 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/jprmaulion/bayesopt-gb-seismic-liquefaction-liq7
Bayesian-optimized gradient boosting for seismic liquefaction prediction with geographic stratified CV on the LIQ/7/2833 global database.
bayesian-optimization binary-classification gradient-boosting lightgbm liquefaction machine-learning python scikit-learn shap shear-wave-velocity soil-mechanics xgboost
Last synced: 29 May 2026
https://github.com/pjaiswalusf/stroke-prediction
This project leverages machine learning to predict stroke risk using XGBoost, Random Forest, and Logistic Regression. It incorporates advanced data preprocessing, class imbalance handling with SMOTE, and hyperparameter optimization using Optuna. Model interpretability is enhanced with SHAP to identify key risk factors.
data-science datapreprocessing logistic-regression machine-learning optuna random-forest shap smote xgboost
Last synced: 25 Jul 2025
https://github.com/hariprasath-v/machinehack_analytics_olympiad_2023
Create a machine learning model to determine the likelihood of a customer defaulting on a loan based on credit history, payment behavior, and account details.
binaryclassification catboost exploratory-data-analysis machine-learning numpy pandas python scikit-learn shap
Last synced: 08 Apr 2026
https://github.com/zuzann18/credit-risk-classification
End-to-end machine learning project for predicting loan defaults on the HMEQ home equity loan dataset. Includes data preprocessing, EDA, feature engineering, model training (Logistic Regression, Random Forest, XGBoost), hyperparameter tuning, model comparison, SHAP-based interpretability, and business recommendations
imbalanced-data logistic-regression mice random-forest-classifier shap smote xgboost
Last synced: 04 Feb 2026
https://github.com/aldotestino/hmi-xai-project
This project uses machine learning to predict diabetes and provides explanations through SHAP and PCA, displayed in an intuitive user interface.
diabetes-prediction drizzle machine-learning nextjs pca shadcn-ui shap tailwindcss xgboost
Last synced: 30 Apr 2026
https://github.com/bintang3703/fraud-detection-credit-mlops
Detect fraud in credit card transactions with an ML pipeline built for production, fast decisions, and clear monitoring
aws-lambda credit-card-fraud-detection credit-scoring data-pipelines data-science deep-learning fastapi fintech fraud-detection imbalanced-learning lightgbm mlflow mlops mlops-project mlops-workflow python shap streamlit
Last synced: 31 Jul 2026
https://github.com/touradbaba/model_engineering
This repository hosts a machine learning tool for breast cancer classification, emphasizing model interpretability. It is deployed on Streamlit Cloud, with a PostgreSQL database for tracking results and data drift, and includes an automated retraining workflow.
crisp-dm datadrift deployment-automation docker github-actions interpretable-machine-learning lime machine-learning mlops model-monitoring postgresql python shap
Last synced: 13 Feb 2026
https://github.com/niisaban/biomedical-ml-tb-biomarker-discovery
Machine learning pipeline for tuberculosis biomarker discovery using bulk transcriptomics, multi-model feature selection, SHAP explainability, and biologically informed interpretation.
bioinformatics biomarker-discovery computational-biology data-science healthcare-ai machine-learning python scikit-learn shap transcriptomics tuberculosis xgboost
Last synced: 01 Aug 2026
https://github.com/skt1803/ai-explanation-tool-grid-explainer
Visual AI explanation tool using grid-based occlusion for CNN interpretability.
cnn explainable-ai grid-explainer grid-layout keras lime masking occlusion-model resnet-50 shap tensorflow visualization
Last synced: 13 Apr 2026
https://github.com/abdul-aa/causal-inference-life-expectancy
Using CausalML to assess the causal impact of a country's development status on its life expectancy
causal-inference causalml shap
Last synced: 14 Mar 2025
https://github.com/wanyingng/visa-approval-prediction
Cut through the red tape of visa processing with this production-ready, end-to-end Machine Learning solution. Built with HTML, CSS, JavaScript, Bootstrap, Python, MongoDB, and FastAPI, the solution leverages a powerful Gradient Boosting Classifier to deliver reasonably accurate predictions through a responsive, user-friendly web interface.
aws bootstrap5 classification docker evidently-ai fastapi github-actions html-css-javascript machine-learning mongodb python3 shap
Last synced: 08 Apr 2026
https://github.com/smit-parekh/deep-demand-forecast-retail
End-to-end Deep Learning (TFT) demand forecasting system for Retail/FMCG with automated MLOps pipeline on Google Cloud (Vertex AI) for inventory optimization. Demonstrates advanced time series modeling, feature engineering, explainability (SHAP), and scalable deployment.
data-science deep-learning demand-forecasting explainable-ai feature-engineering fmcg google-cloud inventory-optimization llmops machine-learning mlops python pytorch retail shap supply-chain temporal-fusion-transformer time-series vertex-ai
Last synced: 19 May 2026
https://github.com/hariprasath-v/machinehack-odetocode_predicting_weather_using_alien_fruit_properties
Identify the type of climate the exoplanet has based on the properties of the fruit by using machine learning.
catboost machine-learning matplotlib numpy pandas seaborn shap sklearn
Last synced: 11 Apr 2026
https://github.com/tirthpatel1020/loan-default-risk-prediction
Explainable ML system for loan default prediction integrating cybersecurity-inspired behavioral features. 99.43% ROC-AUC. Master's thesis project.
credit-risk cybersecurity data-science loan-default machine-learning shap streamlit xgboost
Last synced: 18 Jun 2026
https://github.com/silvano315/churn-prediction-with-shap
This projects aims to classify potential churn customers using a Telco Customer Dataset from IBM. The main applications are about the explainability integration with SHAP algorithm and the creation of interactive notebooks with Exploratory, Classification and Explainability insights.
churn-prediction classification data-science eda explainability ibm machine-learning shap
Last synced: 21 Jul 2025
https://github.com/mahnoorsheikh16/explainable-fake-news-detection-and-personalized-credible-recommendation-via-graphml
System for detecting fake news and suggesting credible alternatives. Takes a news URL and outputs a credibility score, explanation, and top reliable sources. Uses TF-IDF + Logistic Regression, XGBoost, and DistilBERT with hybrid BERT–LightGCN models, plus SHAP and GNNExplainer for interpretability.
bert-embeddings binary-classification distilbert embedding-models fake-news-detection gnn-explainer graphml graphsage lightgcn logistic-regression pytorch recommendation-system shap tf-idf xgboost-classifier
Last synced: 08 Oct 2025
