AI & Machine Learning
Classical Machine Learning
Frame ML problems, engineer and select features, train and tune scikit-learn, XGBoost, LightGBM and CatBoost models, cluster and reduce dimensions, validate without leakage, explain models with SHAP, PDP, LIME and counterfactuals, and build forecasting, survival, recommendation, ranking, fraud and uplift models.
- anomaly-detection-model-builder
- catboost-model-builder
- categorical-encoding-selector
- classification-model-selector
- clustering-algorithm-selector
- collaborative-filtering-implementer
- counterfactual-explanation-generator
- cross-validation-strategy-designer
- dbscan-parameter-tuner
- feature-engineering-idea-generator
- feature-importance-reporter
- feature-scaling-advisor
- feature-selection-analyzer
- feature-store-schema-designer
- fraud-detection-model-designer
- hyperparameter-search-planner
- imbalanced-class-handler
- kmeans-cluster-count-finder
- learning-curve-diagnoser
- learning-to-rank-model-builder
- lime-explanation-generator
- ml-baseline-model-builder
- ml-feasibility-assessor
- ml-model-comparison-reporter
- ml-problem-framing-advisor
- ml-project-scoping-writer
- ml-success-metric-selector
- ml-vs-rules-decision-advisor
- model-card-writer
- optuna-study-writer
- overfitting-underfitting-diagnoser
- partial-dependence-plot-builder
- pca-dimensionality-reducer
- recommendation-system-designer
- regression-model-trainer
- scikit-learn-pipeline-builder
- shap-value-explainer
- survival-analysis-model-builder
- target-leakage-detector
- time-based-feature-builder
- time-series-forecasting-model-builder
- train-test-split-auditor
- umap-tsne-embedding-visualizer
- uplift-model-builder
- xgboost-lightgbm-tuner