Should consist of 20-25 pgs, no images only bullet points

This study explores stock prediction using machine learning (ML) and deep learning (DL) methods, comparing SVM, RF, LSTM, and hybrid models integrating sentiment analysis. It discusses stock factors, challenges of traditional methods, and advantages of modern approaches. The framework employs feature engineering, parameter tuning, and hybrid models for improved accuracy, with datasets preprocessed for optimal performance. Evaluation using MAE, RMSE, and R² shows hybrid models outperform...