SmartAd AB Testing User Analysis

10 Academy Batch 6 - Weekly Challenge: Week 2 - A/B Hypothesis Testing: Ad campaign performance

Table of content

• Introduction
• Overview
• Install
• Data
• Notebooks
• Models
• Scripts
• Test
• Authors

Introduction

As a Machine learning engineer, our tasks is to design a reliable hypothesis testing algorithm for the BIO service and to determine whether a recent advertising campaign resulted in a significant lift in brand awareness.

Overview

• Learning Outcomes

  Statistical Modelling

Using core data science python libraries pandas, matplotlib, seaborn, scikit-learn

ML algorithms Logistic regression, Decision Trees, XGBoost

Model management (building ML catalog contains model feature labels and training model version)

MLOps with DVC, CML, and MLFlow

Install

git clone https://github.com/Ad-Campaign-Performance/abtest-mlops.git
cd abtest-mlops
pip install -r requirements.txt

Data

• The BIO data for this project is a “Yes” and “No” response of online users to the following question

Do you know the brand Lux?

• Yes
• No

Data can be found here at google drive

The data collected for this challenge has the following columns

• auction_id: the unique id of the online user who has been presented the BIO.
• experiment: which group the user belongs to - control or exposed.
• date: the date in YYYY-MM-DD format
• hour: the hour of the day in HH format.
• device_make: the name of the type of device the user has e.g. Samsung
• platform_os: the id of the OS the user has.
• browser: the name of the browser the user uses to see the BIO questionnaire.
• yes: 1 if the user chooses the “Yes” radio button for the BIO questionnaire.
• no: 1 if the user chooses the “No” radio button for the BIO questionnaire.

Notebooks

All the Data Processing, EDA, statistical and sequential Analysis notebook file can be found in the notebooks folder.

Models

All the models generated will be found here in the models folder. All the databases schema will be found here in the models folder.

Scripts

All the Utils for Data munipulation and Ploting can be found here

Tests

All the unit and integration tests are found here in the tests folder.

Authors

👤 Anteneh Tilaye

• GitHub: Anteneh Tilaye
• LinkedIn: Anteneh Tilaye
• Website: Anteneh Tilaye Demo Porfolio

👤 Birhanu Gebisa

• GitHub: Birhanu Gebisa
• LinkedIn: Birhanu Gebisa
• Website: Birhanu Gebisa Demo Porfolio

👤 Genet Shanko

• GitHub: Genet Shanko
• LinkedIn: Genet Shanko
• Website: Genet Shanko Demo Porfolio

👤 Yishak Tadele

• GitHub: Yishak Tadele
• LinkedIn: Yishak Tadele
• Website: Yishak Tadele Porfolio

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