Learning Distributed Word Representations with Neural Network: an implementation from scratch in Octave

In this article, the problem of learning word representations with neural network from scratch is going to be described. This problem appeared as an assignment in the Coursera course Neural Networks for Machine Learning, taught by Prof. Geoffrey Hinton from the University of Toronto in 2012. In this article we will design a neural net language model. The model will learn to predict the next word given the previous three words.