google / doubleml-pipeline
Automated Double Machine Learning (DoubleML + AutoML) pipeline for causal inference — estimate incremental impact, CATE & ROI of promotions, pricing and media.
Why this job: works in the areas we cover, but does not say which job it does
What it does
- AutoML nuisance models. FLAML searches and tunes the learners you list
- Model selection with repetitions. candidates are ranked by a combined
- Heterogeneous effects (CATE). B-spline bases over the covariates you
- Sensitivity analysis (OVB). robustness values and benchmark covariates
- Saturation DML (optional). Phase 0 estimates diminishing returns
Get started
pip install doubleml-pipeline- Maintenance
- Active
- Last commit today
- Stars
- 109
- +13 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 3
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 0 merged
- 0 waiting
- Releases
- None
- Never published
Similar repos
| Repo | Stars | Last commit | Licence | Downloads for |
|---|---|---|---|---|
| DoubleML / doubleml-for-py | 799 | yesterday | BSD-3-Clause | No downloads |
| py-why / EconML | 4,850 | 9 days ago | Custom | No downloads |
| brycewang-stanford / StatsPAI | 373 | today | MIT | No downloads |
More: languages, topics and project record
Languages
- Python 100%
Topics
- automl
- causal-inference
- causal-ml
- debiased-machine-learning
- double-machine-learning
- doubleml
- econometrics
- flaml
- heterogeneous-treatment-effects
- machine-learning
- marketing-analytics
- marketing-mix-modeling
Project record
- JobOther AI tools
- StatusListed
- Commits45
- Forks12
- Watching3
- Stars in 28 days+39
- CreatedMay 29, 2026
- First seen by usNov 7, 2026
- CheckedNov 12, 2026