The project team constructed machine learning models for stock price prediction with 9-year time series data. We predicted whether the stock price would rise or fall by developing machine learning models—Support Vector Machine (SVM), Logistic Regression, Gradient Boosting, Decision Tree, and Random Forest. The SVM model got the best AUC score (0.62). We predicted the stock price with Long-Short Term Memory (LSTM) and ARIMA model.
The presentation slides are also available here.
