FMZennaro / CausalInference
Illustration of counterfactual inference following Ferenc Huszar example
☆12Updated last month
Related projects: ⓘ
- Causai is a Python package for Causality in Machine Learning. We provide state-of-the-art causal algorithms and ML into decision-making s…☆12Updated 3 years ago
- Causal Inference Using Quasi-Experimental Methods☆20Updated 3 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆56Updated last year
- Repo for PyData 2018 tuorial☆12Updated 5 years ago
- Time Series Forecasting and Imputation☆48Updated 2 years ago
- Companion code for my PyData talk: "Introduction to Probabilistic Programming with PyMC3"☆13Updated 5 years ago
- Ananke named for the Greek primordial goddess of necessity and causality, is a python package for causal inference using the language o…☆13Updated 4 years ago
- A method for estimating causal effects in time-series data. Uses available data to automatically find natural experiments for identifying…☆15Updated 4 years ago
- Performance estimation for time series forecasting tasks☆36Updated 3 years ago
- 🪜 Bayesian Hierarchical Models at Scale☆50Updated 3 years ago
- ☆22Updated 4 years ago
- State Space Estimation of Time Series Models in Python: Statsmodels☆42Updated 7 years ago
- List of python packages for causal inference☆17Updated 2 years ago
- Materials Collection for Causal Inference☆37Updated last year
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Notes for short course on econometrics in Stan☆10Updated 7 years ago
- An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learn…☆14Updated 5 years ago
- Machine learning based causal inference/uplift in Python☆56Updated 9 months ago
- A framework for generating complex and realistic datasets for use in evaluating causal inference methods.☆29Updated 3 years ago
- In which I play with the ideas surrounding causality☆49Updated 2 years ago
- A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.☆51Updated 3 months ago
- PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3☆15Updated 6 years ago
- Basic time series modeling with Stan and Pystan☆32Updated 7 years ago
- Tutorial for PyData London 2019 on AB Test by cluster☆14Updated 5 years ago
- Code used in the causality course (401-4632-15) at ETH Zurich.☆19Updated 5 years ago
- Resources to learn more about Machine Learning and Artificial Intelligence☆27Updated 3 years ago
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆57Updated 4 years ago
- Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds☆11Updated 4 years ago
- A full example for causal inference on real-world retail data, for elasticity estimation☆45Updated 3 years ago
- Repository with code, notebook and slides for my talk at PyConDE & PyData Berlin 2019☆36Updated last year