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

Time Series Forecasting – Creating a Multi-Step Forecast in Python

Time series forecasting is about estimating the future value of a time series on the basis of past data. Many time series problems can be solved by looking a single step into the future. I have recently covered this topic … Continued

Visualizing COVID-19 Cases on a Heat Map using GeoPandas and Python

Currently, there is a great need to provide relevant information on COVID-19. Geographic heat maps are particularly suitable for this purpose. A geographical heat map shows a map in which different regions or elements of the map, e.g. countries, cities, … Continued

Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?

Since the sudden emergence of COVID-19, financial markets have experienced turbulent times. A sharp slump in the stock markets was followed by a sharp rise from mid-2020 onwards, bringing stock indices back to record highs by the end of the … 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

Stock Market Prediction – Building a Univariate Model using Keras Recurrent Neural Networks in Python

Forecasting the price of financial assets has fascinated researchers and analysts for many decades. While traditional prediction methods of technical analysis and fundamental analysis are still widely used, interest is now increasingly steering towards automated predictions with machine learning. A … Continued