Code behind aurimas.eu blog posts

A Python package for statistical analysis of A/B tests.

Friends don't let friends make certain types of data visualization - What are they and why are they bad.

Repository with data, starter notebooks, and solution notebooks for my course Applied Time Series Forecasting in Python

Advanced Python Mastery (course by @dabeaz)

AutoML for causal inference.

Open-source Python library for statistical analysis of randomised control trials (A/B tests)

Clickstream Analytics [Blog] https://www.databricks.com/blog/2023/03/21/using-real-time-propensity-estimation-drive-online-sales.html

This python project is a helper package that uses power analysis to calculate required sample size for any experiment

The implementation of GTMF(Ground Truth Maturity Framework)

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms

This repository is a central website describing the 2022 Many Economists Project

This is the repository for the slides used in the Seattle University Econometrics course

A containerized service for scaling up A/B test analysis

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.

My coursework about experimentation and causal inference (aka. a/b testing)

Demonstration of experimentation analysis approach, including A/B testing, A/A testing, and quasi-experimental testing for data driven product decision making.

Behavioral "black-box" testing for recommender systems

Causal Inference Crash Course for Scientists

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) code from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross vali…