Let us Extract some Topics from Text Data — Part III: Non-Negative Matrix Factorization (NMF) | by Seungjun (Josh) Kim | Dec, 2022
Learn more about the unsupervised algorithm derived from linear algebra that uses an intuitive approach to topic modellingFree for Use Photo from PexelsTopic modeling is a type of Natural Language Processing (NLP) task that utilizes unsupervised learning methods to extract out the main topics of some text data we deal with. The word “Unsupervised” here means that there are no training data that have associated topic labels. Instead, the algorithms try to discover the underlying patterns, in this case, the topics, directly…