gaurav -female swati -female shubha -female number of end letters accuracy rajesh -female gaurav -female swati -female shubha -female in the above outputwe can see that accuracy in maximum number of end letters are two and it is decreasing as the number of end letters are increasing topic modelingidentifying patterns in text data we know that generally documents are grouped into topics sometimes we need to identify the patterns in text that correspond to particular topic the technique of doing this is called topic modeling in other wordswe can say that topic modeling is technique to uncover abstract themes or hidden structure in the given set of documents we can use the topic modeling technique in the following scenariostext classification with the help of topic modelingclassification can be improved because it groups similar words together rather than using each word separately as feature recommender systems with the help of topic modelingwe can build the recommender systems by using similarity measures algorithms for topic modeling topic modeling can be implemented by using algorithms the algorithms are as followslatent dirichlet allocation(ldathis algorithm is the most popular for topic modeling it uses the probabilistic graphical models for implementing topic modeling we need to import gensim package in python for using lda slgorithm latent semantic analysis(ldaor latent semantic indexing(lsithis algorithm is based upon linear algebra basically it uses the concept of svd (singular value decompositionon the document term matrix