Alternatives and similar repositories for boltzmannclean

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

• ogrisel / pygbm
  Experimental Gradient Boosting Machines in Python with numba.
  ☆189Updated 7 years ago
• MLBazaar / BTB
  A simple, extensible library for developing AutoML systems
  ☆175Updated 2 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 7 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• genixpro / hypermax
  Better, faster hyper-parameter optimization
  ☆113Updated 2 years ago
• EpistasisLab / scikit-mdr
  A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
  ☆126Updated 7 months ago
• minerva-ml / steppy
  Lightweight, Python library for fast and reproducible experimentation
  ☆136Updated 7 years ago
• ArtificialIntelligenceToolkit / conx
  The On-Ramp to Deep Learning
  ☆96Updated last year
• AlexIoannides / pymc-example-project
  Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
  ☆105Updated 6 years ago
• caioaao / wolpert
  A stacked generalization framework. Built on top of scikit learn
  ☆58Updated 3 years ago
• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• ericmjl / bayesian-deep-learning-demystified
  In which I try to demystify the fundamental concepts behind Bayesian deep learning.
  ☆122Updated 8 years ago
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆101Updated 6 years ago
• MLWave / koolmogorov
  Koolmogorov is a Python library based on CompLearn
  ☆70Updated 8 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 8 years ago
• georgian-io-archive / automl_benchmark
  Distributed, large-scale, benchmarking framework for rigorous assessment of automatic machine learning repositories, projects, and librar…
  ☆30Updated 3 years ago
• bhargavvader / pycobra
  python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.
  ☆125Updated 5 years ago
• canyon289 / bayesian-model-evaluation
  Presented at Scipy Conference 2019
  ☆127Updated 5 years ago
• MLBazaar / MLBlocks
  A library for composing end-to-end tunable machine learning pipelines.
  ☆122Updated 11 months ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆67Updated 7 years ago
• Laurae2 / CategoricalAnalysis
  Analysis of Categorical Encodings for dense Decision Trees
  ☆41Updated 8 years ago
• vinayprabhu / Network_Science_Meets_Deep_Learning
  Designing Deep neural network architectures using topologies from the world of Complex Networks/network Science
  ☆91Updated 6 years ago
• rasbt / DeepLearning-Gdansk2019-tutorial
  Ordinal Regression tutorial for the International Summer School on Deep Learning 2019
  ☆70Updated 6 years ago
• lmc2179 / bayesian_bootstrap
  bayesian bootstrapping in python
  ☆123Updated 3 years ago
• yandexdataschool / MLatGradDays
  Course of Machine Learning in Science and Industry at Heidelberg university
  ☆47Updated 8 years ago
• pymc-learn / pymc-learn
  pymc-learn: Practical probabilistic machine learning in Python
  ☆232Updated 4 years ago
• bbli / ml_board
  a machine learning dashboard that displays hyperparameter settings alongside visualizations, and logs the scientist's thoughts throughout…
  ☆129Updated 3 years ago
• AI-DI / Brancher
  A user-centered Python package for differentiable probabilistic inference
  ☆203Updated 5 years ago
• zygmuntz / gaussrank
  Preparing continuous features for neural networks with GaussRank
  ☆45Updated 7 years ago