Projects

Covid19 Tweet Text Sentiment Classification

Build a sentiment analysis model using NLP techniques to analyze Twitter text related to COVID-19. The final results showed that the best-performing model achieved an accuracy of 83% in classifying tweet sentiment.

Water Bottle Images Classification

Developed a machine learning CNN model that achieves 85% accuracy in classifying water bottle images based on their water levels. Implemented preprocessing techniques and testing GradSearhCV

Airline Passenger Satisfaction

Analyze and provide valuable insights on what aspects of the flight experience have the most impact on passenger satisfaction. A developed machine learning model that predicts passenger satisfaction yield accuracy AUC Score 0.96

KickStarter EDA

Analyzed Kickstarter data to uncover insights for successful campaigns and suggested tips for future project owners