Forecasting Criminal Activity in San Francisco using XGBoost and Python

I recently came across an interesting Kaggle contest that involves predicting different types of criminal activity in San Francisco. Not surprisingly, in a huge city like San Francisco, numerous crimes occur daily. Among the most commonly reported are vehicle theft, … Continued

Anyone About to Leave? Predicting Customer Churn of a Telecommunications Provider

Telecommunications service providers face considerable pressure to expand and retain their subscriber base. One of the biggest cost factors are customers cancelling their contracts. Innovative service providers therefore have learned to use machine learning to predict which of their customers … Continued

Hyperparameter Tuning of a Random Forest Classifier using Grid Search in Python

The functionality of machine learning models can be controlled with their hyperparameters. The choice of these parameters often has a significant impact on model performance and, in practice, can make the difference between sufficient and outstanding performance. Data scientists therefore … Continued