Case Study 1: Marketing & Advertising

Marketing
& Advertising

The Challenge:

Find a reliable way to predict the type of engagement (likes, replies, retweets or retweets with comment) that a user will opt for in relation to a given tweet.

The Solution:

Using text from tweets and anonymized account information, we created a deep learning model that could predict how users would interact or engage with tweets they see on Twitter.

The Outcome:

We built a system that could predict the type and probability of engagement for a particular tweet by a specific user. We achieved a very similar PRAUC-RCE to the state of the art model. 

Tech Tools & Skills Applied:

Apache Spark, Hadoop, TensorFlow, AWS EMR, AWS EC2 and AWS S3.

Results


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