Topic Modeling using Latent Dirichlet Allocation with Python
Topic modeling is a subcategory of unsupervised machine learning method, and a clustering task in particular. The main purpose of a topic model is assigning topics to unlabeled text documents., for example, a typical application is the categorization of social media blog into categories, such as sports, finance, world news, politics, and local news. The specific technique applied in topic modeling is called Latent Dirichlet Allocation (LDA). LDA is a Bayesian statistical approach that tries Read more…