Alternatives and similar repositories for decision-weights

Users that are interested in decision-weights are comparing it to the libraries listed below

• HHammond / kcbo
  A Bayesian testing framework written in Python.
  ☆94Updated 10 years ago
• fonnesbeck / multilevel_modeling
  Tutorial on multilevel modeling, using Gelman radon example
  ☆58Updated 9 years ago
• usnistgov / pmml_pymcBN
  ☆42Updated 6 years ago
• bikestra / bdapy
  Reproducing plots of Bayesian Data Analysis (Gelman et al, 3rd Edition) in Python
  ☆45Updated 10 years ago
• mimno / anchor
  Mallet-compatible anchor-based topic model
  ☆38Updated 11 years ago
• fonnesbeck / PyMC3_EUSS
  Course in Probabilistic Programming in Python for the 2018 EU Summer School
  ☆23Updated 7 years ago
• aflaxman / pymc-examples
  PyMC Example Notebooks
  ☆74Updated 11 years ago
• lendle / SuPyLearner
  An implementation of the SuperLearner algorithm in Python based on scikit-learn.
  ☆25Updated 11 years ago
• rgiordan / LinearResponseVariationalBayesNIPS2015
  Code and text for our NIPS 2015 paper on linear response variational Bayes
  ☆19Updated 7 years ago
• IainNZ / ORSoftwareTools2014
  Repository for code/examples/instructions for the MIT course 15.S60 "Software Tools for Operations Research"
  ☆25Updated 10 years ago
• probcomp / cgpm
  Library of composable generative population models which serve as the modeling and inference backend of BayesDB.
  ☆25Updated 11 months ago
• rgerkin / pystan-sklearn
  ☆32Updated 7 years ago
• civisanalytics / muffnn
  Multilayer Feed-Forward Neural Network predictive model implementations with TensorFlow and scikit-learn
  ☆46Updated 2 years ago
• mwhoffman / pygp
  Python package for inference with Gaussian processes
  ☆11Updated 10 years ago
• ronojoy / pylearn
  Bayesian machine learning in Python
  ☆76Updated 9 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 7 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 6 years ago
• avehtari / PSIS
  Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave
  ☆77Updated last year
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 years ago
• coreylynch / sklearn-transform
  Collection of scripts for doing common transformations in machine learning
  ☆21Updated 12 years ago
• JuliaCon / presentations
  Presentations for JuliaCon
  ☆69Updated 9 years ago
• balajiln / pgbart
  Particle Gibbs for Bayesian Additive Regression Trees
  ☆32Updated 10 years ago
• rgrosse / compositional_structure_search
  ☆46Updated 11 years ago
• napsternxg / ipython-notebooks
  Some iPython Notebooks I have created for personal learning
  ☆65Updated last year
• dwf / glmnet-python
  Wrappers of Jerome Friedman's coordinate-descent Fortran implementation of lasso/elastic net regression from the R "glmnet" package.
  ☆33Updated 15 years ago
• JuliaStats / PGM.jl
  A Julia framework for probabilistic graphical models.
  ☆53Updated 5 years ago
• hstrey / Hidden-Markov-Models-pymc3
  Implementation of Hidden Markov Models in pymc3
  ☆61Updated 8 years ago
• mrtzh / Ladder.jl
  A reliable leaderboard algorithm for machine learning competitions
  ☆17Updated 10 years ago
• tbroderick / mlss2015_bnp_tutorial
  ☆24Updated 9 years ago
• slipguru / adenine
  ADENINE: A Data ExploratioN PipelINE
  ☆15Updated 6 years ago