Alternatives and similar repositories for onelearn

Users that are interested in onelearn are comparing it to the libraries listed below

• MaxHalford / starboost
  Gradient boosting on steroids
  ☆28Updated 11 months ago
• pyensemble / wildwood
  Advanced random forest methods in Python
  ☆57Updated last year
• dataiku-research / cardinal
  A practical Active Learning python package with a strong focus on experiments.
  ☆51Updated 2 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆77Updated last year
• openml-labs / gama
  An automated machine learning tool aimed to facilitate AutoML research.
  ☆99Updated 9 months ago
• thuijskens / scikit-hyperband
  A scikit-learn compatible implementation of hyperband
  ☆76Updated 5 years ago
• brendanhasz / probflow
  A Python package for building Bayesian models with TensorFlow or PyTorch
  ☆174Updated 2 years ago
• probml / bandits
  Bayesian Bandits
  ☆68Updated last year
• elephaint / pgbm
  Probabilistic Gradient Boosting Machines
  ☆154Updated last year
• online-ml / light-river
  WIP
  ☆34Updated 10 months ago
• JohnGoertz / Gumbi
  Gaussian Process Model Building Interface
  ☆50Updated 2 months ago
• malmgrek / gammy
  Generalized additive models in Python with a Bayesian twist
  ☆78Updated last year
• rapidsai / gputreeshap
  ☆98Updated last month
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆74Updated last year
• XAI-ANITI / ethik
  A toolbox for fair and explainable machine learning
  ☆55Updated 11 months ago
• guillermo-navas-palencia / cprior
  Fast Bayesian A/B and Multivariate testing.
  ☆36Updated 2 years ago
• raphaelsty / abayes
  Autoregressive Bayesian linear model
  ☆21Updated 4 years ago
• pafoster / pyitlib
  A library of information-theoretic methods for data analysis and machine learning, implemented in Python and NumPy.
  ☆94Updated 2 weeks ago
• AlCorreia / GeFs
  Generative Forests in Python
  ☆35Updated last year
• manuel-calzolari / shapicant
  Feature selection package based on SHAP and target permutation, for pandas and Spark
  ☆30Updated 3 years ago
• StatMixedML / DGBM
  Distributional Gradient Boosting Machines
  ☆27Updated 2 years ago
• MaxHalford / naked
  The simplest way to deploy a machine learning model
  ☆23Updated 2 years ago
• sdpython / mlinsights
  Extends scikit-learn with new models, transformers, metrics, plotting.
  ☆73Updated 2 months ago
• scikit-learn-contrib / skglm
  Fast and modular sklearn replacement for generalized linear models
  ☆173Updated last week
• ealcobaca / pymfe
  Python Meta-Feature Extractor package.
  ☆133Updated 11 months ago
• lorentzenchr / model-diagnostics
  Tools for diagnostics and assessment of (machine learning) models
  ☆35Updated 3 months ago
• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆28Updated 4 years ago
• soda-inria / hazardous
  Competing Risks and Survival Analysis
  ☆102Updated 2 weeks ago
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 3 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago