Alternatives and similar repositories for advanced-comp-2017

Users that are interested in advanced-comp-2017 are comparing it to the libraries listed below

• fonnesbeck / PyMC3_Oslo
  Probabilistic programming in Python workshop at Oslo universitetssykehus HF
  ☆36Updated 9 years ago
• jfpuget / Tidy-Data
  Python code for Hadley Whickham's article on Tidy Data.
  ☆35Updated 9 years ago
• mrocklin / dask-workshop
  ☆28Updated 8 years ago
• lendle / SuPyLearner
  An implementation of the SuperLearner algorithm in Python based on scikit-learn.
  ☆25Updated 11 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 7 years ago
• odewahn / computational-publishing
  ☆67Updated 8 years ago
• rlabbe / statistical-rethinking
  Notebooks containing R code from Richard McElreath's Statistical Rethinking
  ☆72Updated 9 years ago
• TomAugspurger / postlearn
  Common post-estimation tasks for scikit-learn
  ☆17Updated 9 years ago
• AllenDowney / BayesForUndergrads
  Materials for a workshop on developing undergraduate classes on Bayesian statistics.
  ☆47Updated 9 years ago
• HHammond / kcbo
  A Bayesian testing framework written in Python.
  ☆93Updated 11 years ago
• stitchfix / diamond
  Python solver for mixed-effects models
  ☆97Updated 8 months ago
• szilard / GBM-multicore
  GBM multicore scaling: h2o, xgboost and lightgbm on multicore and multi-socket systems
  ☆20Updated 7 years ago
• amueller / advanced_git_nyu_2016
  Advanced git and github course material
  ☆40Updated 7 years ago
• szilard / xgboost-adv-workshop-LA
  Advanced workshop on XGBoost with Tianqi Chen in Santa Monica, June 2, 2016
  ☆27Updated 9 years ago
• GalvanizeDataScience / pipelines_and_featureunions
  An in depth tutorial on sklearn's Pipeline and FeatureUnion classes.
  ☆16Updated 8 years ago
• cliburn / sta-663-2015
  Course materials for STA663
  ☆37Updated 9 years ago
• TaddyLab / bayesian-forest
  ☆31Updated 9 years ago
• itsrainingdata / sparsebn
  Software for learning sparse Bayesian networks
  ☆42Updated 5 years ago
• davharris / mcmc-tutorial
  Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo
  ☆52Updated 12 years ago
• ptoulis / implicit-sgd
  Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.
  ☆16Updated 11 years ago
• AllenDowney / BayesSeminar
  Bayesian statistics seminars
  ☆29Updated 8 years ago
• fonnesbeck / PyMC3_EUSS
  Course in Probabilistic Programming in Python for the 2018 EU Summer School
  ☆23Updated 7 years ago
• thedataincubator / practical-ml
  ☆24Updated 7 years ago
• Quantia-Analytics / DyDataSF2016Visualization
  Materials for the PyData San Francisco 2016 visualization tutorial
  ☆14Updated 9 years ago
• jupyter / ngcm-tutorial
  Materials for the IPython/Jupyter workshop at the NGCM Summer Academy, at Southampton University, Boldrewood campus.
  ☆47Updated 8 years ago
• GaelVaroquaux / sklearn_europython_2014
  Scikit-learn Tutorial at EuroPython 2014
  ☆43Updated 7 years ago
• ledell / h2oEnsemble-benchmarks
  Benchmarks of the H2O Ensemble R interface (H2O 2.0).
  ☆14Updated 5 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 8 years ago
• napsternxg / ipython-notebooks
  Some iPython Notebooks I have created for personal learning
  ☆65Updated last year
• djsutherland / skl-groups
  scikit-learn addon to operate on set/"group"-based features
  ☆41Updated 9 years ago