Sentiment Classification with Natural Language Processing on LSTM

LSA itself is an unsupervised way of uncovering synonyms in a collection of documents.To start, we take a look how Latent Semantic Analysis is used in Natural Language Processing to analyze relationships between a set of documents and the terms that they contain. Then we go steps further to analyze and classify sentiment. We will review Chi Squared for feature selection along the way. We will use Recurrent Neural Networks, and in particular LSTMs, to perform sentiment analysis in Keras. Since, text is the most unstructured form of all the available data, various types of noise are present in it and the data is not readily analyzable without any pre-processing.