During the time I was attending the Master’s course Advanced Data Analytics for Management Support, we were given the opportunity to work with real data to conduct predictive analytics on Medium articles, to predict the number of claps every article can potentially get. To address this challenge, I built a hybrid classification-regression pipeline. Used article metadata and tags with feature engineering and model evaluation to tackle challenges such as sparse exposure and unique Medium user behavior.
