Lord of the Machines

a data science / machine learning hackathon designed to discover the best data scientists in the community.

• Problem Statement

Email Marketing is still the most successful marketing channel and the essential element of any digital marketing strategy. Marketers spend a lot of time in writing that perfect email, labouring over each word, catchy layouts on multiple devices to get them best in-industry open rates & click rates.

How can I build my campaign to increase the click-through rates of email? - a question that is often heard when marketers are creating their email marketing plans.

Can we optimize our email marketing campaigns with Data Science?

It's time to unlock marketing potential and build some exceptional data-science products for email marketing.

Analytics Vidhya sends out marketing emailers for various events such as conferences, hackathons, etc. We have provided a sample of user-email interaction data from July 2017 to December 2017. You are required to predict the click probability of links inside a mailer for email campaigns from January 2018 to March 2018.

Data set can be found on Analytics Vidya

DATASET DESCRIPTION

• campaign_data.csv

Contains the features related to 52 email Campaigns

• train.csv

Contains the click and open information for each user corresponding to given campaign id (Jul 17 - Dec 17)

• test.csv

Contains the user and campaigns for which is_click needs to be predicted (Jan 18 - Mar 18)

EVALUATION METRIC

The evaluation metric for this competition is AUC-ROC score.

PUBLIC AND PRIVATE SPLIT

Note that the test data is further randomly divided into Public (30%) and Private (70%) data. Your initial responses will be checked and scored on the Public data.

The final rankings would be based on your private score which will be published once the competition is over.

I have been ranked 147 among 3594 contestants with EXtraTreeClassifier Model

Complete project note book can be found at my github repository