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To enhance the existing stock price prediction project by integrating a Gated Recurrent Unit (GRU) model alongside the existing Long Short-Term Memory (LSTM) model. This will allow for a comparative analysis of the performance of both models on the same dataset.
Use Case
Enhanced Predictive Analysis: Integrating a GRU model into the stock price prediction project will significantly enhance predictive analysis capabilities. By comparing GRU with the existing LSTM model, users can identify which model offers better accuracy and performance for predicting stock prices based on historical data. This comparison will allow for more informed decision-making when choosing the appropriate model for similar time-series forecasting tasks
Benefits
Integrating the GRU model will improve prediction accuracy, offer a faster and more efficient alternative to LSTM, and provide users with greater flexibility for model selection. The feature enhances the project's versatility, making it applicable to broader time-series forecasting tasks and fostering community engagement through comparative analysis.