Alternatives and similar repositories for practical-bayes

Users that are interested in practical-bayes are comparing it to the libraries listed below

• FMenchetti / CausalArima
  An R package to estimate the effect of interventions on univariate time series using ARIMA models
  ☆23Updated last year
• pyartemis / artemis
  A Python package with explanation methods for extraction of feature interactions from predictive models
  ☆30Updated last year
• predict-idlab / cct-cmc
  Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
  ☆16Updated last month
• AngelPone / pyhts
  A python package for hierarchical forecasting, inspired by hts package in R.
  ☆28Updated 5 months ago
• sb-ai-lab / HypEx
  Fast and customizable framework for automatic and quick Causal Inference in Python
  ☆113Updated this week
• aizakharov94 / sibur_challenge_2021
  ☆14Updated 3 years ago
• Techtonique / nnetsauce
  Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks (currently Python & R)
  ☆19Updated last week
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• StatMixedML / Hyper-Trees
  Forecasting with Hyper-Trees
  ☆18Updated 9 months ago
• jgreathouse9 / mlsynth
  This is the repository for the Python library mlsynth
  ☆35Updated this week
• mattblackwell / causalsens
  A sensitivity analysis package for causal effects
  ☆12Updated last year
• juanitorduz / website_projects
  Repository containing the code of the projects presented in my personal website.
  ☆42Updated last week
• lorismichel / drf
  Distributional Random Forests (Cevid et al., 2020)
  ☆43Updated 2 years ago
• RektPunk / MQBoost
  Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost
  ☆33Updated 7 months ago
• robjhyndman / forecasting_workshop
  ☆16Updated 2 years ago
• lancastercmaf / FFT
  Friday Forecasting Talks materials
  ☆11Updated last year
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 3 years ago
• xqnwang / conformalForecast
  Methods and tools for multistep-ahead time series conformal prediction.
  ☆38Updated 3 months ago
• SelfExplainML / GamiNet
  GAMI-Net: Generalized Additive Models with Structured Interactions
  ☆31Updated 3 years ago
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆24Updated 4 years ago
• Techtonique / ahead_python
  Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)
  ☆13Updated 2 weeks ago
• lucasdurand / network-graph-tutorial
  construct a network graph to explore and visualize how people connect in an organisation
  ☆18Updated last year
• kidaufo / StatisticalModeling
  Statistical modeling and Bayesian modeling by PyMC3, Stan and TensorFlow Probability
  ☆23Updated 5 years ago
• hmelberg / causal
  notebooks on methods for causal inference
  ☆34Updated 11 months ago
• Quantco / metalearners
  MetaLearners for CATE estimation
  ☆45Updated this week
• yao-yl / hierarchical-stacking-code
  code and demo for hierarchical stacking paper
  ☆10Updated 4 years ago
• jessegrabowski / statespace-presentation
  Presentation materials for PyMC Statespace
  ☆23Updated 10 months ago
• mainkoon81 / Study-02-AB-Testing
  Hypothesis testing (Parametric/Non-Parametric)
  ☆11Updated 5 years ago
• rizbicki / predictionBands
  R package to compute distribution-free prediction bands using density estimators
  ☆9Updated 3 years ago
• smazzanti / tds_features_important_doesnt_mean_good
  ☆32Updated last year