WillianFuks / tfcausalimpactLinks
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
☆657Updated 10 months ago
Alternatives and similar repositories for tfcausalimpact
Users that are interested in tfcausalimpact are comparing it to the libraries listed below
Sorting:
- A Python package for causal inference in quasi-experimental settings☆1,057Updated this week
- DoubleML - Double Machine Learning in Python☆672Updated this week
- CausalLift: Python package for causality-based Uplift Modeling in real-world business☆350Updated 2 years ago
- AutoML for causal inference.☆231Updated 10 months ago
- Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.☆977Updated this week
- Time should be taken seer-iously☆317Updated 2 years ago
- Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS☆390Updated 3 years ago
- UpliftML: A Python Package for Scalable Uplift Modeling☆330Updated 2 years ago
- Improving XGBoost survival analysis with embeddings and debiased estimators☆341Updated last year
- A Python package for modular causal inference analysis and model evaluations☆797Updated 7 months ago
- A package to compute a marketing mix model.☆72Updated 2 years ago
- Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…☆499Updated 2 weeks ago
- Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.☆712Updated 3 weeks ago
- ☆128Updated last week
- ☆90Updated 2 years ago
- Python package for causal inference using Bayesian structural time-series models.☆243Updated 5 years ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆785Updated 4 months ago
- LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channe…☆1,009Updated 4 months ago
- ☆289Updated 2 years ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆579Updated last year
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆2,011Updated 5 months ago
- Causal Inference in Python☆573Updated 4 months ago
- An extension of XGBoost to probabilistic modelling☆664Updated last week
- Hierarchical Time Series Forecasting with a familiar API☆225Updated 2 years ago
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆435Updated last year
- uplift modeling in scikit-learn style in python☆783Updated 2 years ago
- ☆275Updated 11 months ago
- Fast SHAP value computation for interpreting tree-based models☆545Updated 2 years ago
- Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inf…☆556Updated last week
- A python library to build Model Trees with Linear Models at the leaves.☆387Updated last year