Multivariate Time Series Forecasting with LSTMs in Keras - Machine Learning Mastery

Neural networks like Long Short-Term Memory (LSTM) recurrent neural networks are able to almost seamlessly model problems with multiple input variables. This is a great benefit in time series forecasting, where classical linear methods can be difficult to adapt to multivariate or multiple input forecasting problems. In this tutorial, you will discover how you can develop an LSTM model for multivariate time series forecasting in the Keras deep learning library. This tutorial assumes you have a Python SciPy environment installed. You can use either Python 2 or 3 with this tutorial.