The purpose of this project is to develop a predictive model to assess and classify films reviews as positive or negative.
The notebook SentimentAnalysis.ipynb contains the loaded dataset and trained models.
In the notebook deployment.ipynb the model is deployed. It is loaded and stored at the IBM Cloud, so it can be used to predict sentiment in new reviews.
Tools: SVC, tfidfVEctorizer, RandomForestClassifier, Multilayer Perceptron (MLPClassifier), AdaBoost, VotingClassifier, ROC-AUC score, IBM Cloud, Watson AP
➡️ This project was developed as an activity of the ACAMICA DATA SCIENCE course.