auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

awesome-marketing

A curated list of resources related to internet marketing.

conversionsapi-tag-for-googletagmanager

This repository will contain the artifacts needed for setting up Conversions API implementation on Google Tag Manager's serverside. Please follow the instructions https://www.facebook.com/business/help/702509907046774

data_science_resources

📊 Data Science Resources, Data Science Standards & Machine Learning Pipelines

ecommerce-marketing-spend-optimization

Marketing Budget Optimization for Online Retailers using AI & Machine Learning.

facebook-for-magento2

* Pixel on all pages, which trigger events link, PageView, ViewContent, AddToCart, Initiatecheckout and Purchase.* In the background, Syncs the products from the merchants product catalog to Facebook Catalog.* Stores all the data, like pixel id, catalog id, business maanger id, on to the local database on the instance.

facebook-pixel-for-wordpress

A plugin for advertisers who use Wordpress to enable them easily setup the facebook pixel.

forecastga

A Python tool to forecast Google Analytics data using several popular time series models.

forecasting

Time Series Forecasting Best Practices & Examples by Microsoft

geolift

GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lift) of ad campaign.

google-ads-scripts

Award winning Google Ads Scripts by Brainlabs

hands-on-data-science-for-marketing

Hands-On Data Science for Marketing, published by Packt

infima

A UI framework that provides websites with the minimal CSS and JS needed to get started with building a modern responsive beautiful website

josuegonzalez

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

koala

A lightweight Facebook library supporting the Graph, Marketing, and Atlas APIs, realtime updates, test users, and OAuth.

kudosbot

A slack app + bot that sends kudos to your fellow peers on the workspace.

lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

machine-learning-interview-enlightener

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

marketing-data-science

Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

marketing-for-engineers

A curated collection of marketing articles & tools to grow your product.

mit-15-003-data-science-tools

Study guides for MIT's 15.003 Data Science Tools

mta-calibration-through-conversion-lift

In this research paper, Annalect used Google and Facebook conversion lift studies to calibrate our Multi-Touch Attribution results from Google Ads Data Hub (ADH). We assessed the feasibility of these conversion lift calibrations and the impact of using conversion lift results in the calibration adjustment.

optimate

Sample codes that allows to fetch different Reach and Frequency curves from the Facebook Marketing API.

plugin-marketingcampaignsreporting

probability

Applied Probability Theory for Everyone

project-checklist

✅ A checklist of things to do before releasing your project

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth by Meta

python-for-probability-statistics-and-machine-learning

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

robyn

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.