Alternatives and similar repositories for hypermax

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

• ogrisel / pygbm
  Experimental Gradient Boosting Machines in Python with numba.
  ☆187Updated 6 years ago
• MLBazaar / BTB
  A simple, extensible library for developing AutoML systems
  ☆175Updated 2 years ago
• automl / ParameterImportance
  Parameter Importance Analysis Tool
  ☆77Updated 4 years ago
• AI-DI / Brancher
  A user-centered Python package for differentiable probabilistic inference
  ☆203Updated 5 years ago
• thuijskens / scikit-hyperband
  A scikit-learn compatible implementation of hyperband
  ☆76Updated 5 years ago
• automl / HPOlib1.5
  ☆69Updated 5 years ago
• evhub / bbopt
  Black box hyperparameter optimization made easy.
  ☆76Updated 2 years ago
• udellgroup / oboe
  An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
  ☆84Updated 4 years ago
• ili3p / HORD
  Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
  ☆115Updated 8 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆149Updated last year
• levyben / DeepSuperLearner
  DeepSuperLearner - Python implementation of the deep ensemble algorithm
  ☆135Updated 7 years ago
• gdikov / hypertunity
  A toolset for black-box hyperparameter optimisation.
  ☆136Updated 5 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆183Updated 7 years ago
• EpistasisLab / scikit-mdr
  A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
  ☆125Updated 4 months ago
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆102Updated 6 years ago
• seba-1511 / randopt
  Streamlined machine learning experiment management.
  ☆107Updated 5 years ago
• AIworx-Labs / chocolate
  A fully decentralized hyperparameter optimization framework
  ☆124Updated last year
• automl / BOAH
  BOAH: Bayesian Optimization & Analysis of Hyperparameters
  ☆67Updated 5 years ago
• zygmuntz / gaussrank
  Preparing continuous features for neural networks with GaussRank
  ☆45Updated 7 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆245Updated 3 years ago
• cgnorthcutt / hypopt
  ⏸ Parallelized hyper-param optimization with validation set, not crossval
  ☆91Updated 2 years ago
• sherpa-ai / sherpa
  Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
  ☆342Updated 5 years ago
• LucaAmbrogioni / Brancher
  A python library for stochastic variational inference and differentiable probabilistic programming
  ☆33Updated 6 years ago
• maxim5 / hyper-engine
  Python library for Bayesian hyper-parameters optimization
  ☆91Updated 7 years ago
• aredier / trelawney
  General Interpretability Package
  ☆58Updated 2 years ago
• ldv1 / LinXGBoost
  Extension of the awesome XGBoost to linear models at the leaves
  ☆82Updated 6 years ago
• minerva-ml / steppy
  Lightweight, Python library for fast and reproducible experimentation
  ☆136Updated 6 years ago
• CyberZHG / keras-adabound
  AdaBound optimizer in Keras
  ☆56Updated 5 years ago
• caioaao / wolpert
  A stacked generalization framework. Built on top of scikit learn
  ☆57Updated 2 years ago