causalml (conda): <a href="https://github.com/uber/causalml">   <img src="https://raw.githubusercontent.com/uber/causalml/master/docs/_static/img/logo/causalml_logo.png" alt="CausalML banner" /> </a>  ``Causal ML`` is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research. It provides a standard interface that allows user to estimate the **Conditional Average Treatment Effect** (CATE) or **Individual Treatment Effect** (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention **T** on outcome **Y** for users with observed features **X**, without strong assumptions on the model form.  PyPI: [(https://pypi.org/project/causalml/]((https://pypi.org/project/causalml/)
Keywords: causal-inference|incubation|machine-learning|uplift-modeling