Alternatives and similar repositories for exploratory-notebooks

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

• MasaAsami / pysynthdid
  Synthetic difference in differences for Python
  ☆81Updated last year
• nlapier2 / PySensemakr
  Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
  ☆52Updated 2 weeks ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆50Updated 3 years ago
• shoepaladin / causalinference_crashcourse
  Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
  ☆95Updated last month
• microsoft / SparseSC
  Fit Sparse Synthetic Control Models in Python
  ☆82Updated last year
• bernardodionisi / differences
  difference-in-differences in Python
  ☆100Updated last year
• gdmarmerola / cfml_tools
  My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable an…
  ☆30Updated 2 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated last year
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆46Updated 8 months ago
• sdfordham / pysyncon
  A python module for the synthetic control method
  ☆68Updated last month
• d2cml-ai / mgtecon634_py
  This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…
  ☆12Updated last year
• NickCH-K / causaldata
  Packages of Example Data for The Effect
  ☆139Updated 6 months ago
• juanitorduz / website_projects
  Repository containing the code of the projects presented in my personal website.
  ☆42Updated this week
• PlaytikaOSS / uplift-analysis
  A Python library that implements scoring utilities, analysis strategies, and visualization methods which can serve uplift modeling use-ca…
  ☆24Updated 2 years ago
• d2cml-ai / 14.388_py
  This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …
  ☆16Updated 2 years ago
• valendin / rfm2lstm
  Customer Base Analysis with Recurrent Neural Networks
  ☆18Updated 3 years ago
• kquist / DoubleML-Python
  ☆12Updated 6 years ago
• einatboro / awesome-survival-analysis
  Resources for Survival Analysis
  ☆94Updated 7 months ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆52Updated 3 years ago
• vsemenova / orthoml
  Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…
  ☆25Updated 2 years ago
• jgreathouse9 / mlsynth
  This is the repository for the Python library mlsynth
  ☆29Updated this week
• williambdean / pymc-mlflow-example
  MLflow logging for PyMC
  ☆9Updated 2 months ago
• FMenchetti / CausalArima
  An R package to estimate the effect of interventions on univariate time series using ARIMA models
  ☆20Updated last year
• amazon-science / causal-forecasting
  ☆13Updated last year
• rakshitha123 / WeeklyForecasting
  This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model…
  ☆47Updated 3 years ago
• matteocourthoud / Blog-Posts
  Code and notebooks for my Medium blog posts
  ☆126Updated last year
• keihirano / modern-sampling
  Course Materials for AEA Short Course on Modern Sampling Methods
  ☆29Updated 3 years ago
• ostojanovic / causalML
  ☆33Updated 8 months ago
• AngelPone / pyhts
  A python package for hierarchical forecasting, inspired by hts package in R.
  ☆28Updated 3 months ago
• DoubleML / doubleml-docs
  Documentation and User Guide for DoubleML - Double Machine Learning in Python & R
  ☆21Updated last week