SelfExplainML / PiML-ToolboxLinks
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
β1,285Updated 10 months ago
Alternatives and similar repositories for PiML-Toolbox
Users that are interested in PiML-Toolbox are comparing it to the libraries listed below
Sorting:
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.β1,509Updated last week
- Interpretable ML package π for concise, transparent, and accurate predictive modeling (sklearn-compatible).β1,572Updated 2 months ago
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.β2,475Updated last week
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.β583Updated last year
- Visualize decision trees in Pythonβ524Updated 11 months ago
- Scalable machine π€ learning for time series forecasting.β1,157Updated this week
- π Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Modelsβ3,133Updated last week
- nannyml: post-deployment data science in pythonβ2,124Updated 6 months ago
- Fast SHAP value computation for interpreting tree-based modelsβ553Updated 2 years ago
- Shapley Interactions and Shapley Values for Machine Learningβ681Updated 3 weeks ago
- The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to sβ¦β737Updated last week
- Python package for conformal predictionβ552Updated 3 months ago
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.β622Updated last year
- Compilation of high-profile real-world examples of failed machine learning projectsβ746Updated last year
- Machine learning with dataframesβ1,554Updated this week
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadβ¦β677Updated 11 months ago
- The book every data scientist needs on their desk.β995Updated 4 months ago
- Extra blocks for scikit-learn pipelines.β1,376Updated 2 weeks ago
- Probabilistic Hierarchical forecasting π with statistical and econometric methods.β728Updated last week
- The repository to showcase the best framework for tabular data - the Awesome CatBoostβ281Updated 5 months ago
- A Python package for causal inference in quasi-experimental settingsβ1,098Updated this week
- EvalML is an AutoML library written in python.β843Updated 3 weeks ago
- Predictive Power Score (PPS) in Pythonβ1,172Updated 4 months ago
- Feature engineering and selection open-source Python library compatible with sklearn.β2,190Updated last week
- Time series forecasting with machine learning modelsβ1,434Updated this week
- Human-explainable AI.β529Updated last week
- Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.β1,166Updated 4 months ago
- Track your Data Science. Skore's open-source Python library accelerates ML model development with automated evaluation reports, smart metβ¦β576Updated this week
- Temporian is an open-source Python library for preprocessing β‘ and feature engineering π temporal data π for machine learning applicatiβ¦β709Updated 3 months ago
- Python-centered read-along of Forecasting: Principles and Practiceβ512Updated 4 months ago