An end-to-end machine learning project evaluating baseline and ensemble models to detect rare fraudulent credit card transactions while minimizing false alarms and customer friction.

I created four machine learning models to predict the sentiment (positive or negative) of movie reviews from IMDB. First, I trained the models with a subset of reviews with known review sentiment. Next, I tested model accuracy by predicting review sentiment and comparing determining whether the prediction was correct or incorrect. Then, I selected the most accurate model and tuned its parameters to produce the best possible prediction accuracy.