Alternatives and similar repositories for slim-python

Users that are interested in slim-python are comparing it to the libraries listed below

• TaddyLab / bayesian-forest
  ☆31Updated 8 years ago
• tmadl / sklearn-interpretable-tree
  Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)
  ☆47Updated 4 years ago
• hammerlab / survivalstan
  Library of Stan Models for Survival Analysis
  ☆124Updated 4 years ago
• deaneckles / randomization_inference
  Tutorial in randomization inference, experimental design and analysis, and experiments in networks.
  ☆29Updated 9 years ago
• andland / logisticPCA
  Dimensionality reduction for binary data
  ☆50Updated 4 years ago
• lendle / SuPyLearner
  An implementation of the SuperLearner algorithm in Python based on scikit-learn.
  ☆25Updated 11 years ago
• stitchfix / diamond
  Python solver for mixed-effects models
  ☆97Updated 3 weeks ago
• evidation-opensource / ContinuousTimeMarkovModel
  Continuous-time Markov model with discrete observations
  ☆24Updated 2 years ago
• lopezpaz / causation_learning_theory
  Code for "Towards a learning theory of cause-effect inference" (ICML 2015).
  ☆30Updated 4 years ago
• gelman / ep-stan
  ☆32Updated 4 years ago
• lrouviere / AGB
  These are the codes used in the paper "Accelerated Gradient Boosting" by G. Biau, B. Cadre, and L. Rouvière.
  ☆17Updated 7 years ago
• tmadl / sklearn-random-rotation-ensembles
  Scikit-learn compatible implementations of the Random Rotation Ensemble idea of (Blaser & Fryzlewicz, 2016)
  ☆43Updated 9 years ago
• usnistgov / pmml_pymcBN
  ☆42Updated 6 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• kshedden / Statsmodels-MixedLM
  Teaching materials for Python MixedLM (mixed linear models)
  ☆48Updated 8 years ago
• ptoulis / implicit-sgd
  Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.
  ☆16Updated 10 years ago
• patr1ckm / mvtboost
  Boosted regression trees for multivariate, longitudinal, and hierarchically clustered data.
  ☆36Updated 7 years ago
• itsrainingdata / sparsebn
  Software for learning sparse Bayesian networks
  ☆43Updated 4 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 7 years ago
• BayesianTestsML / tutorial
  Tutorial on Bayesian tests for Machine Learning
  ☆79Updated 4 years ago
• aflaxman / pymc-examples
  PyMC Example Notebooks
  ☆74Updated 11 years ago
• kapelner / ICEbox
  An R package for better visualizing a statistical learning model
  ☆35Updated 2 years ago
• amueller / patsylearn
  Patsy Adaptors for Scikit-learn
  ☆48Updated 6 years ago
• ck37 / varimpact
  Variable importance through targeted causal inference, with Alan Hubbard
  ☆57Updated 3 weeks ago
• swager / randomForestCI
  This package is DEPRECATED. Please use the packages `grf` or `ranger` instead, which have built-in confidence intervals.
  ☆70Updated 7 years ago
• jonsedar / tsne_presentation
  Quick & dirty repo for hosting the Notebook for t-SNE presentation at delivered at Python Quants and PyData London meetups
  ☆9Updated 9 years ago
• airoldilab / sgd
  An R package for large scale estimation with stochastic gradient descent
  ☆62Updated last year
• ofirnachum / uncertainty_gbm
  Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data
  ☆26Updated 9 years ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆67Updated 7 years ago
• rbas2015 / CausalFX
  CausalFX R Package
  ☆13Updated 10 years ago