rakutentech / spark-dirty-cat

Related projects: ⓘ

• FlorianWilhelm / lda4rec
  🧮 Extended Latent Dirichlet Allocation for Collaborative Filtering in Recommender Systems.
  ☆40Updated 2 years ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated last year
• koaning / scikit-partial
  Pipeline components that support partial_fit.
  ☆42Updated 2 months ago
• ing-bank / industry2vec
  ☆28Updated 5 years ago
• online-ml / river-extra
  Extra functionalities for river
  ☆14Updated 4 months ago
• jacopotagliabue / retail-personalization-workshop
  In-Session Personalization Workshop for eCommerce, April 2021, and the MICES Workshop in June 2021.
  ☆21Updated 3 years ago
• koaning / scikit-fairness
  this repo might get accepted
  ☆29Updated 3 years ago
• koaning / scikit-prune
  Prune your sklearn models
  ☆19Updated last year
• ralphhaygood / sklearn-gbmi
  scikit-learn gradient-boosting-model interactions
  ☆25Updated last year
• pcerda / string_categorical_encoders
  Scripts for paper "Encoding high-cardinality string categorical variables"
  ☆24Updated 5 years ago
• AdiVarma27 / pyAB
  Python package for Bayesian & Frequentist A/B Testing
  ☆11Updated last year
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• MaxHalford / starboost
  Gradient boosting on steroids
  ☆26Updated 3 months ago
• AidanCooper / shap-clustering
  How to use SHAP values for better cluster analysis
  ☆51Updated 2 years ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆50Updated 3 years ago
• oakfr / intro-to-reco
  introduction class to recommendation systems
  ☆22Updated 5 years ago
• paypal / Iguanas
  ☆67Updated this week
• linkedin / TE2Rules
  Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
  ☆40Updated 4 months ago
• Shopify / bevel
  Ordinal regression in Python
  ☆65Updated 3 months ago
• microsoft / CBM
  Cyclic Boosting Machines - an explainable supervised machine learning algorithm
  ☆57Updated 2 weeks ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆41Updated last year
• ing-bank / spark-matcher
  Record matching and entity resolution at scale in Spark
  ☆31Updated 10 months ago
• criteo / CriteoDisplayCTR-TFOnSpark
  ☆27Updated 2 years ago
• microsoft / rankerEval
  A fast numpy-based implementation of ranking metrics for information retrieval and recommendation.
  ☆31Updated 2 years ago
• ml-tue / automated-string-cleaning
  Repository for my master thesis on automated string handling
  ☆16Updated 3 years ago
• guillermo-navas-palencia / clogistic
  Logistic regression with bound and linear constraints. L1, L2 and Elastic-Net regularization.
  ☆33Updated last year
• tlentali / leab
  📈🔍 Lets Python do AB testing analysis
  ☆75Updated 5 months ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆35Updated 3 years ago
• guillermo-navas-palencia / cprior
  Fast Bayesian A/B and Multivariate testing.
  ☆36Updated last year
• aslakey / CBM_Encoding
  CBM Encoding
  ☆19Updated 3 years ago