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Natural Language Processing Project: Utilizing NLTK and Python to process and analyze the Reuters-21578 dataset, enhancing text retrieval through advanced tokenization, stemming, and stop word removal, along with implementing query processing and ranking mechanisms.
a comprehensive tool designed to evaluate the sentiment of movie reviews. Hosted the ML model as a REST API, easily accessible from any application using json request.
In this data cleaning has been done with the help of nltk library and other library which include wordnetlimmitizer , ,and steaming of word has been donw by portersteammer ,
A Search engine that searches for a phrase or word in local text files using stemming and indexing, and returns the matches, in order of relevance, using the tf-idf Algorithm.
Information Retrieval Model to the research interests of the Faculty members of the Department (a.k.a. DEP or professors) and based on this to suggest possible collaborations between them.
Classification of tweets into positive and negative using classifiers like SVM, Logistic Regression, Naive bayes. Implementation of porter stemmer algorithm.