This article focuses on using a Deep LSTM Neural Network architecture to provide multidimensional time series forecasting using Keras and Tensorflow - specifically on stock market datasets to provide momentum indicators of stock price.

The following article sections will briefly touch on LSTM neuron cells, give a toy example of predicting a sine wave then walk through the application to a stochastic time series. The article assumes a basic working knowledge of simple deep neural networks.

## Time Series Forecasting with the Long Short-Term Memory Network in Python - Machine Learning Mastery

The Long Short-Term Memory recurrent neural network has the promise of learning long sequences of observations. It seems a perfect match for time series forecasting, and in fact, it may be. In this tutorial, you will discover how to develop an LSTM forecast model for a one-step univariate time series forecasting problem. After completing this …

Course materials and notes for Stanford class CS231n: Convolutional Neural Networks for Visual Recognition.

The Developmental Approach to Natural and Artificial Intelligence for integrated vision, audition, touch, language, reasoning, robotics and the brain-mind