Clustering Text with k-Means

In the last post, we talked about Topic Modeling or a way to identify several topics from a corpus of documents. The method used there was Latent Dirichlet Allocation or LDA. In this article, we're going to perform a similar task but through the unsupervised machine learning method of clustering. While the method is different, the outcome is several groups (or topics) of words related to each other. For this example, we will use the Wine Reviews dataset from Kaggle.