We have mentioned that we have been using a layer size of 100 while training the Word2Vec model. This means that there can be 100 features and, eventually, a 100-dimensional feature space. It is impossible to plot a 100-dimensional space, and therefore we rely on t-SNE to perform dimensionality reduction. In this recipe, we will generate 2D plots from the Word2Vec model.