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Zindi User Behaviour Birthday Challenge

Domain:

digital infrastructure

Record type:

dataset

Can you predict which users will be active on Zindi in the next month?
The data is a subset of Zindi user activity. All variables have been masked to preserve privacy.
The objective of this competition is to create a machine learning model to determine if a user will be active on Zindi in the next month. An active user is one that enters a competition, makes a submission or engages through the discussion forums. Just imagine, you are one of the data points in this challenge!
competitions.csv: this file contains information about hackathons and competitions
CompetitionPartipation.csv: this file contains information about users' participation in hackathons and competitions
users.csv: this file contains information about the users such as when they registered and which country they are from
submissions.csv: this file contains information about each submission made
discussions.csv: this file contains information about every discussion made, such as which userID made the submission and when it was created
comments.csv: this file contains information about every comment made, such as which userID made the submission and when it was made
VariableDefinitions.csv: this file contains information about each table and each variable
train.csv - this is a summarized table of the above activities. You can use this table to train you model but it is recommended you pull features from the above tables to enrich your model.
test.csv - contains the userID, month and year you need to apply your model to.
SampleSubmission.csv - shows the submission format for this competition. The order of the rows does not matter, but the names of the ‘ID’ must be correct.