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. As you can imagine, in a massive city like San Francisco, numerous crimes happen every day. Crime statistics distinguish between 39 … Continued

Six Common Error Metrics for Measuring Regression Errors in Machine Learning

This article presents six error metrics that are commonly used to measure regression errors in machine learning. Measuring errors is an important step in developing a predictive model and the basis for evaluating a model’s performance. However, a universal error … Continued

Stock Market Prediction – Adjusting Time Series Prediction Intervals in Python

In a previous article on stock market forecasting, we have created a forecast for the S&P500 stock market index using a neural network and Python. The prediction interval used in this previous article was a single day. However, many time-series … Continued