LauraAnn Migliore, Ph.D. has successfully completed a project on Twitter Sentiment Analysis for Airline Services to identify the sentiment from a tweet (positive, neutral, or negative) and gain deeper insights on airlines' customer satisfaction. Data was preprocessed (via tokenization, removal of special characters, punctuations, etc., and lemmatization). Applied count vectorizer and Tf-IDF vectorizer and fit the model using vectorized column with cross validation. Model was evaluated using confusion matrix and review of the top 40 features via word cloud plot. #HandsOnProject #Workingwithtext #Vectorization #Countvectorizer #TfIDFvectorizer #Sentimentanalysis #Parametertuning #Confusionmatrixbasedmodelevaluation #MyGreatLearning #universityoftexas
