Alternatives and similar repositories for hypertools-paper-notebooks:

Users that are interested in hypertools-paper-notebooks are comparing it to the libraries listed below

• tmadl / sklearn-interpretable-tree
  Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)
  ☆47Updated 4 years ago
• bbli / ml_board
  a machine learning dashboard that displays hyperparameter settings alongside visualizations, and logs the scientist's thoughts throughout…
  ☆128Updated 2 years ago
• stitchfix / diamond
  Python solver for mixed-effects models
  ☆97Updated 7 years ago
• brannondorsey / keras_weight_animator
  Save keras weight matrices as short animated videos during training
  ☆105Updated 7 years ago
• dask / dask-searchcv
  dask-searchcv is now part of dask-ml: https://github.com/dask/dask-ml
  ☆240Updated 6 years ago
• amueller / advanced_training
  Advanced Scikit-learn training session
  ☆118Updated 8 years ago
• ronojoy / pylearn
  Bayesian machine learning in Python
  ☆76Updated 9 years ago
• EFavDB / linselect
  ☆89Updated 6 years ago
• kylemcdonald / Coloring-t-SNE
  Exploration of methods for coloring t-SNE.
  ☆218Updated 8 years ago
• ferrine / gelato
  Bayesian dessert for Lasagne
  ☆84Updated 7 years ago
• lmc2179 / bayesian_bootstrap
  bayesian bootstrapping in python
  ☆121Updated 3 years ago
• jmcarpenter2 / parfit
  A package for parallelizing the fit and flexibly scoring of sklearn machine learning models, with visualization routines.
  ☆199Updated last year
• jfsantos / keras-tutorial
  Tutorial teaching the basics of Keras and some deep learning concepts
  ☆104Updated 8 years ago
• rhiever / sklearn-benchmarks
  A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.
  ☆212Updated 7 years ago
• strawlab / best
  Bayesian estimation supersedes the t test
  ☆144Updated 3 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 6 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆184Updated 6 years ago
• fonnesbeck / PyMC3_DataScienceLA
  PyMC3 tutorial for DataScience LA (January 2017)
  ☆67Updated 6 years ago
• Britefury / deep-learning-tutorial-pydata
  Deep learning tutorial for PyData
  ☆85Updated 6 years ago
• alexandraj777 / machine-learning-samples
  Sample applications built using AWS' Amazon Machine Learning.
  ☆51Updated 7 years ago
• jnothman / searchgrid
  Helpers for constructing scikit-learn grid search
  ☆38Updated 5 years ago
• drckf / paysage
  Unsupervised learning and generative models in python/pytorch.
  ☆119Updated 2 years ago
• atavory / ibex
  Pandas Adapters For Scikit-Learn
  ☆53Updated 6 years ago
• sigopt / sigopt-sklearn
  SigOpt wrappers for scikit-learn methods
  ☆75Updated last year
• Kaixhin / FGLab
  Future Gadget Laboratory
  ☆222Updated 7 years ago
• 0011001011 / vizuka
  Explore high-dimensional datasets and how your algo handles specific regions.
  ☆107Updated 6 years ago
• christophebourguignat / notebooks
  ☆160Updated 8 years ago
• rdipietro / jupyter-notebooks
  ☆79Updated 7 years ago
• szilard / benchm-dl
  Playing with various deep learning tools and network architectures
  ☆70Updated 7 years ago
• alvarouc / polyssifier
  run a multitude of classifiers on you data and get an AUC report
  ☆68Updated last year