Stock Market Forecasting Neural Networks for Multi-Output Regression in Python

Multi-output regression Python Neural Networks

Multi-output time series regression can forecast several steps of a time series at once. The number of neurons in the final output layer determines how many steps the model can predict. Models with one output return single-step forecasts. Models with various outputs can return entire series of time steps and … Read more

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

stock market prediction Python tutorial

Regression models based on recurrent neural networks (RNN) can recognize patterns in time series data, making them an exciting technology for stock market forecasting. What distinguishes these RNNs from traditional neural networks is their architecture. It consists of multiple layers of long-term, short-term memory (LSTM). These LSTM layers allow the … Read more

Stock Market Prediction – Adjusting Time Series Prediction Intervals in Python

stock market prediction python

This tutorial shows how to adjust prediction intervals in time series forecasting using Keras recurrent neural networks and Python. We build on a previous article on stock market forecasting, in which we created a forecast for the S&P500 stock market index. The prediction interval used in this last article was … Read more