causalml VS upliftml

Compare causalml vs upliftml and see what are their differences.

causalml

Uplift modeling and causal inference with machine learning algorithms (by uber)

upliftml

UpliftML: A Python Package for Scalable Uplift Modeling (by bookingcom)
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causalml upliftml
10 7
4,698 306
3.3% 2.3%
8.4 0.0
5 days ago about 1 year ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

causalml

Posts with mentions or reviews of causalml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-13.

upliftml

Posts with mentions or reviews of upliftml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-26.

What are some alternatives?

When comparing causalml and upliftml you can also consider the following projects:

EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.

causallift - CausalLift: Python package for causality-based Uplift Modeling in real-world business

Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

BTYD - BTYD 2.4.3

BTYDplus - R package for Customer Behavior Analysis

CausalPy - A Python package for causal inference in quasi-experimental settings

genome_integration - MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.

db-benchmark - reproducible benchmark of database-like ops