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Title: GitHub - uber/causalml: Uplift modeling and causal inference with machine learning algorithms · GitHub

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Description: Uplift modeling and causal inference with machine learning algorithms - uber/causalml

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[1]https://github.com/uber/causalml#Literature
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https://github.com/uber/causalml#workshops-talks-and-publications
3rd Workshop on Causal Inference and Machine Learning in Practicehttps://causal-machine-learning.github.io/kdd2025-workshop/
2nd Workshop on Causal Inference and Machine Learning in Practicehttps://causal-machine-learning.github.io/kdd2024-workshop/
Causal Inference and Machine Learning in Practice: Use cases for Product, Brand, Policy and Beyondhttps://causal-machine-learning.github.io/kdd2023-workshop/
Causal Data Science Meeting 2021https://www.causalscience.org/meeting/program/day-2/
2021 Conference on Digital Experimentation @ MIT (CODE@MIT)https://ide.mit.edu/events/2021-conference-on-digital-experimentation-mit-codemit/
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uberhttps://causal-machine-learning.github.io/kdd2021-tutorial/
CausalML: Python package for causal machine learninghttps://arxiv.org/abs/2002.11631
Uplift Modeling for Multiple Treatments with Cost Optimizationhttps://ieeexplore.ieee.org/document/8964199
2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)http://203.170.84.89/~idawis33/dsaa2019/preliminary-program/
Feature Selection Methods for Uplift Modelinghttps://arxiv.org/abs/2005.03447
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