Python Deep Learning Projects

Plotting the word cluster using the t-SNE algorithm

So, after our analysis, we know that our word2vec model has learned some concepts from the provided corpus, but how do we visualize it? Because we have created a 300-dimensional space to learn the features, it's practically impossible for us to visualize. To make it possible, we will use a dimension reduction algorithm, called t-SNE, which is very well known for reducing a high dimensional space into more humanly understandable two or three-dimensional space.

"t-Distributed Stochastic Neighbor Embedding (t-SNE) (https://lvdmaaten.github.io/tsne/) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. ...