This project is a sentiment analysis of 50k movie reviews on Internet Movie Database (IMDB) and the dataset is available on: IMDB dataset of 50k movie reviews

SentimentAnalysis_IMDBReviews.ipynb consists of the following steps:

Preprocessing:

• Lowercasting
• Removing URLs
• Removing Punctuations
• Removing Stopwords
• Handling Emogies
• stemming

vectorizing using TF-IDF

building, training and testing the model using 3 methods:

• Logistic Regression
• Random Forest Classifier
• Decision Tree Classifier

At the end, Logistic Regression turned out to be the best model, with accuracy score of 0.8941