Alternatives and similar repositories for causal_ai

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

• matheusfacure / exploratory-notebooks
  Unstructured Code with interesting analysis
  ☆36Updated last year
• takechanman1228 / Effective-Uplift-Modeling
  ☆25Updated last year
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆52Updated 4 years ago
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆66Updated 3 years ago
• AlxndrMlk / causality
  Notes, exercises and other materials related to causal inference, causal discovery and causal ML.
  ☆162Updated last month
• rabia174 / ConformaSight
  Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.
  ☆26Updated last year
• marcopeix / AppliedTimeSeriesForecastingInPython
  Repository with data, starter notebooks, and solution notebooks for my course Applied Time Series Forecasting in Python
  ☆66Updated 6 months ago
• slavakx / bayesian_mmm
  Code for the article Modeling Marketing Mix using PyMC3
  ☆27Updated 3 years ago
• ostojanovic / causalML
  ☆34Updated last year
• MLDreamer / Linkedin-posts
  ☆25Updated last month
• matteocourthoud / Blog-Posts
  Code and notebooks for my Medium blog posts
  ☆131Updated last year
• Valdecy / pyInterDemand
  A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES
  ☆39Updated 2 years ago
• supplyseer-ai / supplyseer
  Python library for Applied Computational Supply Chain & Logistics. Unlock Neural Nets, Bayesian EOQ, Optimization, Time Series, and more …
  ☆105Updated 3 weeks ago
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆64Updated 4 years ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆74Updated this week
• causalens / cai-causal-graph
  A Causal AI package for causal graphs.
  ☆61Updated 3 weeks ago
• kvnkho / pydata-timeseries-forecasting
  Material for PyData NYC Tutorial on Large Scale Timeseries Forecasting
  ☆27Updated 2 years ago
• matheusfacure / causal-inference-in-python-code
  Code for the Book Causal Inference in Python
  ☆365Updated 2 years ago
• ksureshkumar-loveshark / blogs_public
  ☆13Updated 5 years ago
• profitopsai / ProRCA
  ☆22Updated 10 months ago
• takechanman1228 / mmm_pydata_global_2022
  ☆28Updated 2 years ago
• py-why / causaltune
  AutoML for causal inference.
  ☆236Updated last year
• KishManani / m5-forecasting-tutorial
  An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.
  ☆20Updated 3 years ago
• shoepaladin / causalinference_crashcourse
  Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
  ☆115Updated last month
• smazzanti / valicast
  Validation for forecasts
  ☆17Updated 2 years ago
• slavakx / medium_posts
  ☆92Updated 2 years ago
• modeva-ai / Modeva
  Integrated tool for model development and validation
  ☆33Updated 3 months ago
• rick12000 / confopt
  A Library for Conformal Hyperparameter Tuning
  ☆104Updated 2 months ago
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆192Updated last week
• Carl-McBride-Ellis / TOBoML
  The Orange Book of Machine Learning
  ☆56Updated 5 months ago