In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Customer churn remains a huge issue for telcos, but AI could be the key to changing that. Or, it could fail to live up to its promises.

Abstract: Uplift Modeling can be an effective machine learning method when identifying the potential customers who have the highest possibility of creating a positive impact on the marketing ...

A machine learning project that analyzes telecom customer data to predict churn using Logistic Regression, Decision Tree, and Random Forest models. Built with Python, scikit-learn, and data ...

Abstract: The goal of predicting subscriptions for OTT (Over-The-Top) platforms using machine learning is to devise a model which can accurately predict whether a customer will continue using this ...

With the cost of acquiring new app installs skyrocketing, keeping users engaged who have already installed is critical for maximizing acquisition spend and customer lifetime value. Urban Airship’s ...