Alternatives and similar repositories for pymc-marketing:

Users that are interested in pymc-marketing are comparing it to the libraries listed below

• sibylhe / mmm_stan
  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
  ☆375Updated 2 years ago
• google / lightweight_mmm
  LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channe…
  ☆948Updated last month
• pymc-labs / CausalPy
  A Python package for causal inference in quasi-experimental settings
  ☆958Updated this week
• WillianFuks / tfcausalimpact
  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
  ☆632Updated 2 months ago
• facebookincubator / GeoLift
  GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lif…
  ☆195Updated 8 months ago
• facebookexperimental / Robyn
  Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is…
  ☆1,252Updated last week
• station-10 / awesome-marketing-machine-learning
  A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference…
  ☆101Updated 10 months ago
• google / matched_markets
  Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.
  ☆82Updated last week
• jamalsenouci / causalimpact
  Python port of CausalImpact R library
  ☆281Updated 10 months ago
• slavakx / medium_posts
  ☆86Updated last year
• Garve / mamimo
  A package to compute a marketing mix model.
  ☆70Updated last year
• DP6 / Marketing-Attribution-Models
  Python Class created to address problems regarding Digital Marketing Attribution.
  ☆323Updated 5 months ago
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆58Updated 3 years ago
• Minyus / causallift
  CausalLift: Python package for causality-based Uplift Modeling in real-world business
  ☆346Updated last year
• google / tfp-causalimpact
  ☆100Updated last year
• Nixtla / hierarchicalforecast
  Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
  ☆633Updated this week
• facebookincubator / LTVision
  LTVision is an open-source library from Meta, designed to empower businesses to unlock the full potential of predicted customer lifetime …
  ☆75Updated this week
• matheusfacure / causal-inference-in-python-code
  Code for the Book Causal Inference in Python
  ☆293Updated last year
• ColtAllen / btyd
  Buy Till You Die and Customer Lifetime Value statistical models in Python.
  ☆115Updated 10 months ago
• takechanman1228 / mmm_pydata_global_2022
  ☆27Updated last year
• DoubleML / doubleml-for-py
  DoubleML - Double Machine Learning in Python
  ☆558Updated last week
• DavisTrey / ExperimentationResources
  A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms
  ☆155Updated last year
• carl24k / fight-churn
  Code from the book Fighting Churn With Data
  ☆282Updated last month
• bookingcom / upliftml
  UpliftML: A Python Package for Scalable Uplift Modeling
  ☆324Updated last year
• eeghor / mta
  Multi-Touch Attribution
  ☆113Updated 3 years ago
• jrkinley / game-theory-attribution
  Data-Driven Marketing Attribution
  ☆32Updated 4 years ago
• MBrouns / timeseers
  Time should be taken seer-iously
  ☆314Updated 2 years ago
• google / trimmed_match
  This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for…
  ☆65Updated last year
• pymc-devs / pymc-examples
  Examples of PyMC models, including a library of Jupyter notebooks.
  ☆311Updated this week
• spotify / confidence
  ☆268Updated 3 months ago