diff --git a/.all-contributorsrc b/.all-contributorsrc index bd5cb5ad4..2cbac7833 100644 --- a/.all-contributorsrc +++ b/.all-contributorsrc @@ -256,6 +256,14 @@ "code", "bug" ] - }, + { + "login": "maniktyagi04", + "name": "Manik Tyagi", + "avatar_url": "https://avatars.githubusercontent.com/u/74643036?v=4", + "profile": "https://github.com/maniktyagi04", + "contributions": [ + "doc" + ] + } ] } diff --git a/docs/source/related_software.rst b/docs/source/related_software.rst index 6274c5d79..ea7e3bca8 100644 --- a/docs/source/related_software.rst +++ b/docs/source/related_software.rst @@ -4,4 +4,54 @@ Related Software ================ -TODO +The following is a curated list of software packages related to ``skpro`` +in the probabilistic prediction and scientific Python ecosystem. + +Probabilistic Prediction & Forecasting +--------------------------------------- + +`sktime `_ + A unified framework for time series machine learning in Python. + ``skpro`` is maintained by the same community and integrates with ``sktime`` + to enable probabilistic forecasting pipelines: an ``sktime`` probabilistic + forecaster can be built from an ``skpro`` probabilistic regressor. + +`ngboost `_ + Natural Gradient Boosting for probabilistic prediction. + ``skpro`` provides a native interface to ``ngboost`` estimators via the + ``NGBoostRegressor`` and ``NGBoostSurvival`` classes. + +`cyclic-boosting `_ + A Python package for probabilistic prediction using cyclic boosting algorithms. + ``skpro`` provides a native interface to ``cyclic-boosting`` estimators. + +Uncertainty Quantification & Conformal Prediction +-------------------------------------------------- + +`MAPIE `_ + Model Agnostic Prediction Interval Estimator. + A library for uncertainty quantification via conformal prediction, compatible + with ``scikit-learn``. ``skpro`` can interface with MAPIE for interval + and quantile prediction. + +Machine Learning Foundations +----------------------------- + +`scikit-learn `_ + The standard Python machine learning library. + ``skpro`` is fully ``scikit-learn``-compatible and ``scikit-base``-compliant, + extending ``scikit-learn`` regressors with probabilistic prediction capabilities. + +Survival & Time-to-Event Analysis +----------------------------------- + +`lifelines `_ + A complete survival analysis library for Python, implementing a wide range + of parametric and non-parametric survival models. + +Probabilistic Programming +-------------------------- + +`pymc `_ + A probabilistic programming library in Python for Bayesian statistical modeling + and inference using Markov Chain Monte Carlo (MCMC) and variational inference.