Keywords - Natural Language Processing, Machine Learning, Python, NLTK, scikit-learn

• Built and trained machine learning models to analyse and classify the binary sentiment of a movie review in the dataset of IMDB movie reviews containing 50,000 movie reviews.
• Experimented with and tuned Decision Tree, Naïve Bayes and SVM models for the classification, achieving accuracy of 87.4% with Linear SVM model with frequency bag-of-words text representation.

• Code folder contains python code files to pre-process the raw text data and train the machine learning models
  • The set of python files generate_dataset_*.py clean and pre-processe the text data
  • model_training_bagOfwords.py trains several machine learning models using bag-of-words text representation
  • model_training_freqency_bagOfwords.py trains several machine learning models using frequency bag-of-words text representation
• Dataset folder contains the raw as well as the pre-processed dataset
• At Root location
  • Project Presentation (Sentiment Analysis - Project Presentation - Final.pdf)