Alternatives and similar repositories for pycobra

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

• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 6 years ago
• caioaao / wolpert
  A stacked generalization framework. Built on top of scikit learn
  ☆57Updated 2 years ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆67Updated 7 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 8 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• EpistasisLab / scikit-mdr
  A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
  ☆125Updated 3 months ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• lmc2179 / bayesian_bootstrap
  bayesian bootstrapping in python
  ☆121Updated 3 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• wdm0006 / sklearn-extensions
  A consolidated package of small extensions to scikit-learn
  ☆24Updated 2 years ago
• numeristical / introspective
  Repo for the ML_Insights python package
  ☆152Updated 5 months ago
• JackCaster / Intro_to_PyMC3
  Short introduction to Bayesian statistical modelling with PyMC3
  ☆18Updated 5 years ago
• pymc-learn / pymc-learn
  pymc-learn: Practical probabilistic machine learning in Python
  ☆230Updated 4 years ago
• ottogroup / dstoolbox
  Tools that make working with scikit-learn and pandas easier.
  ☆44Updated last week
• MLBazaar / BTB
  A simple, extensible library for developing AutoML systems
  ☆175Updated 2 years ago
• skylergrammer / SimulatedAnnealing
  ☆45Updated 4 years ago
• parsing-science / pymc3_quickstart_guide
  ☆80Updated 8 years ago
• canyon289 / bayesian-model-evaluation
  Presented at Scipy Conference 2019
  ☆127Updated 5 years ago
• interpretable-ml / iml
  Interpretable ML package designed to explain any machine learning model.
  ☆61Updated 7 years ago
• mpearmain / gestalt
  A helper library for data science pipeline
  ☆36Updated 6 years ago
• ogrisel / pygbm
  Experimental Gradient Boosting Machines in Python with numba.
  ☆185Updated 6 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• jmcarpenter2 / parfit
  A package for parallelizing the fit and flexibly scoring of sklearn machine learning models, with visualization routines.
  ☆199Updated last year
• amueller / advanced_training
  Advanced Scikit-learn training session
  ☆118Updated 9 years ago
• jnothman / searchgrid
  Helpers for constructing scikit-learn grid search
  ☆38Updated 5 years ago
• Laurae2 / CategoricalAnalysis
  Analysis of Categorical Encodings for dense Decision Trees
  ☆41Updated 8 years ago
• levyben / DeepSuperLearner
  DeepSuperLearner - Python implementation of the deep ensemble algorithm
  ☆135Updated 7 years ago
• MLWave / koolmogorov
  Koolmogorov is a Python library based on CompLearn
  ☆70Updated 8 years ago
• ericmjl / bayesian-deep-learning-demystified
  In which I try to demystify the fundamental concepts behind Bayesian deep learning.
  ☆123Updated 7 years ago