Word2Vec (skip-gram model): PART 1 - Intuition. – Towards Data Science – Medium

The skip-gram neural network model is actually surprisingly simple in its most basic form. Train a simple neural network with a single hidden layer to perform a certain task, but then we're not actually going to use that neural network for the task we trained it on! Instead, the goal is actually just to learn the weights of the hidden layer–we'll see that these weights are actually the "word vectors" that we're trying to learn. We're going to train the neural network to do the following. Given a specific word in the middle of a sentence (the input word), look at the words nearby and pick one at random.