Twitter US Airline Sentiment Analysis

Using Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn

• Analyzing customer attitudes towards airlines in the United States based on a Twitter dataset using Natural Language Processing and Machine Learning techniques..

• Applied NLTK for data processing and vectorization, and addressed label imbalance with up-sampling.

• Developed a Random Forest model, tuning hyperparameters via Grid Search CV and Random Search CV, to predict customer attitudes and estimate model accuracy.