Stock-Market Prediction using Neural Networks for Multi-Output Regression in Python

This article showcases multi-output neural networks for time-series regression and demonstrates their use in the context of stock market forecasting. We will train and test a Keras neural network with ten output neurons using historical price quotes for Apple stock. … Continued

Building a Twitter Bot for Crypto Trading Signals using Python

In this article, we will develop a Twitter bot in Python that will generate automated trading signals. Our bot will pull real-time price data on various cryptocurrencies (Bitcoin, Ethereum, Doge, etc.) from the crypto exchange Gate.io and analyze it using … Continued

Feature Engineering for Multivariate Time Series Prediction with Python

Multivariate time series forecasting models often do not rely exclusively on historical time series data but use additional features such as moving averages or momentum indicators. The underlying assumption is that multiple variables increase the accuracy of a forecast by … Continued

Stock Market Prediction using Multivariate Time Series and Recurrent Neural Networks in Python

Time series forecasting has become a popular domain for applying deep learning technologies and recurrent neural networks in recent years. Regression models based on recurrent neural networks can recognize patterns in large data sets and thus make more accurate predictions … Continued

Evaluate the Performance of Time Series Forecasting Models with Python

The evaluation of the prediction quality is a crucial step in the development of regression models. To evaluate regression models, we measure the deviation between predictions and actual values in numerical terms. Therefore, unlike classification models, regression models allow for … 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

Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python

We can solve many time forecasting problems by looking at a single step into the future. However, some forecasting problems require us to understand how a signal will develop over a more extended period so that it is not enough … Continued