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

Python Cheat Sheet: Measuring Prediction Errors in Time Series Forecasting

Measuring prediction errors in time series forecasting Measuring prediction errors is an important step in the process of developing a predictive machine learning model. In time series forecasting, model performance is typically measured with different error metrics, each of which … Continued

Stock Market Prediction – Adjusting Time Series Prediction Intervals

Time series prediction is a hot topic of machine learning. In a previous post on stock market forecasting, I have shown how you can build a prediction model for the S&P500 Stock Market Index. The prediction interval used in this … Continued