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

Forecasting Beer Sales with ARIMA in Python

ARIMA (Auto Regressive Integrated Moving Average) is a useful statistical modelling technique for time series forecasting. Compared to machine learning, ARIMA is a classical modeling technique that is very strong especially when the time series to be analyzed follows a clear … Continued