Skip to content

A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more

License

Notifications You must be signed in to change notification settings

station-10/awesome-marketing-machine-learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 

Repository files navigation

Awesome Maintenance GitHub GitHub GitHub GitHub

awesome-marketing-machine-learning

A curated list of awesome machine learning libraries for marketing. Inspired by both awesome-production-machine-learning and awesome-machine-learning, and created and maintained by Station 10.

Note that some packages could fit into more than one section. This has been noted in the descriptions so be sure to Ctrl + F as well as exploring by sections.

Want to contribute? Please raise a Pull Request or an issue. If you find this useful please drop a ⭐️. This helps motivate us and others to update and maintain the list.

All packages are Python based unless otherwise stated. We welcome contributions from R Users!

Main Content

Attribution

Causal Inference

  • CausalImpact Github Stars (R) Causal Inference using Bayesian structural time-series models by Google.
  • causalml Github Stars Uplift modeling and causal inference with ML by Uber.
  • CausalPy Github Stars Causal Inference & Synthetic Control. Supports fitting with scikit-learn and PyMC models.
  • dowhy Github Stars Causal Inference that supports explicit modeling and testing of causal assumptions.
  • SyntheticControlMethods Github Stars Causal inference using Synthetic Control.
  • tfcausalimpact Github Stars Google's CausalImpact Algorithm implemented on top of TensorFlow Probability.
  • upliftml Github Stars Scalable unconstrained and constrained uplift modeling from experimental data using PySpark and H20.
  • scikit-uplift Github Stars
  • Uplift modeling python package that provides fast sklearn-style models implementation, evaluation metrics and visualization tools.

Churn / CLV

Data

  • gapandas4 Github Stars Python package for querying the Google Analytics Data API for GA4 and displaying the results in a Pandas dataframe.

Econometrics

  • EconML Github Stars AI, Econometrics and Causal Inference modelling.
  • statsmodels Github Stars Statistical modeling including time series and econometrics.

Geo Experimentation

  • trimmed_match Github Stars Ad effectiveness through the design and analysis of randomized Geo Experiments by Google.
  • matched_markets Github Stars Time-Based regression matched markets approach for designing Geo Experiments by Google.
  • GeoexperimentsResearch Github Stars (R) Open-source implementation of the geo experiment analysis methodology developed at Google (Archived)
  • GeoLift Github Stars Geo Experimentation methodology based on Synthetic Control Methods used to measure lift of ad campaigns by Facebook.

Media / Marketing Mix Models

  • BayesianMMM Github Stars Bayesian Media Mix mMdelling with shape and carryover effect.
  • dammmdatagen Github Stars (R) Media Mix Modeling Data Generator.
  • lightweight-mmm Github Stars Bayesian Media Mix Models by Google.
  • mamimo Github Stars Small Media Mix Models designed to be used in conjunction with ML libraries (e.g. SKL)
  • mmm-stan Github Stars Multiplicative Media Media Mix Model.
  • pymc-marketing Github Stars Bayesian Media Mix, Adstock, Saturation Customer Lifetime Value & Churn models.
  • Robyn Github Stars (R) Bayesian Media Mix Models by Facebook.

Personalisation / Segmentation

  • amazon-denseclus Github Stars Python module for clustering both categorical and numerical data using UMAP and HDBSCAN by Amazon.
  • rfm Github Stars RFM Analysis and Customer Segmentation.
  • retentioneering-tools Github Stars Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation
  • ecommercetools Github Stars Data science toolkit for those working in technical ecommerce, marketing science, and technical seo and includes a wide range of features to aid analysis and model building.

Recommendation Systems

  • lightfm Github Stars Implementation of LightFM, a hybrid recommendation algorithm.
  • openrec Github Stars Open-source and modular library for neural network-inspired recommendation algorithms.
  • recmetrics Github Stars A library of metrics for evaluating recommender systems
  • recommenders Github Stars Best Practices on Recommendation Systems by Microsoft.
  • Surprise Github Stars Scikit for building and analyzing recommender systems that deal with explicit rating data.

Time Series

  • darts Github Stars Python library for user-friendly forecasting and anomaly detection on time series built using SKL conventions.
  • gluonts Github Stars Probabilistic time series modeling, focusing on deep learning based models, based on PyTorch and MXNet.
  • neural_prophet Github Stars Framework for interpretable time series forecasting built on PyTorch.
  • orbit Github Stars Python package for Bayesian time series forecasting and inference by Uber.
  • pmdarima Github Stars
  • Pmdarima is a statistical library designed to fill the void in Python's time series analysis capabilities.
  • prophet Github Stars Additive time series modelling by Facebook.
  • sktime Github Stars A unified framework for ML with Time Eeries.
  • statsforecast Github Stars Lightning ⚡️ fast forecasting with statistical and econometric models.
  • stumpy Github Stars STUMPY computes something called the matrix profile, which is just an academic way of saying "for every subsequence automatically identify its corresponding nearest-neighbor"
  • temporian Github Stars Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖.
  • tbats Github Stars BATS and TBATS time series forecasting
  • tsfresh Github Stars Time Series Feature extraction based on scalable hypothesis tests.
  • tslearn Github Stars The machine learning toolkit for time series analysis in Python.

Survival Analysis

  • lifelines Github Stars lifelines is a pure Python implementation of the best parts of survival analysis.
  • pysurvival Github Stars An open source python package for Survival Analysis modeling.
  • scikit-survival Github Stars Survival analysis built on top of scikit-learn.

Synthetic Control

  • pysyncon Github Stars Multiple Synthetic Control implementations.
  • scpi Github Stars Provides Python, R and Stata implementations of estimation and inference procedures for synthetic control methods.
  • SparseSC Github Stars Sparse Synthetic Control Models in Python by Microsoft.

Synthetic Data

  • Decoy Github Stars Synthetic Data Generator using DuckDB at its core.
  • SDV Github Stars Python library designed to be your one-stop shop for creating tabular synthetic data.

Releases

No releases published

Packages

No packages published