Robyn是Meta Marketing Science的一个实验性、AI/ML驱动的开源营销组合建模(MMM)包。我们的使命是使建模知识民主化,通过创新激励行业,减少建模过程中的人为偏见,并建立一个强大的开源营销科学社区。
mmm 开源项目推荐(144 个)
mmm 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 144 个仓库Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
LightweightMMM收件箱是一个轻量级的Bayesian Marketing Mix建模(MMM)库,允许用户轻松训练MMM并获取渠道归因信息。
Analytics & Machine Learning R Sidekick
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
Shows home assistant sensors on the Magic Mirror.
该项目在 GitHub 上没有填写描述
(ml) - python implementation of bayesian media mix modelling with shape and carryover effect
该项目在 GitHub 上没有填写描述
A simple Marketing Mix Modeling library for Python
PonziStory 2.0 is a clone of the Popular Tradermoni p2p script. A typical Get Help and Provide help Script like MMM with top notch functionalities. Get Secured and Updated Clone Scripts. Investment, hyip,trading and ponzi scripts etc. Scripts like Ammdefi clone scripts, Afriq Arbitrage System(AAS) clone scripts, etc. in all
A module for the MagicMirror 2 that adds touch buttons for showing/hiding other modules.
🚌🚏🚅 Displays information about the upcoming departure of public transport within Germany, NRW. Module for MagicMirror
Marketing Science in Python — a practical guide to marketing analytics, causal inference, marketing mix modeling, pricing, forecasting, and customer analytics.
🔌 A MagicMirror² Module bitcoin ticker
This is my MagicMirror
MagicMirror2 module for TFL (Transport for London) Lines Status
PySiMMMulator is an open source Python marketing simulation package, which allows users to generate simulated data to use in testing Marketing Mix Models (MMMs).
Ask your WorkMagic marketing data anything — attribution, lift tests and budget plans in Claude, ChatGPT, Codex, Cursor, Copilot and Gemini.
Simba — Bayesian Marketing Mix Modeling (MMM) platform. Media attribution, budget optimization, incrementality measurement, and scenario planning. Built on PyMC-Marketing. No-code, fully transparent, enterprise-ready.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/mmm。
- 该话题在 GitHub 上共有 144 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 4714 Star,覆盖 6 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。