ML Stock Prediction System
A sophisticated deep learning ecosystem designed to decode market volatility. Leveraging LSTM architectures and automated feature engineering to transform raw financial data into actionable market insights.
The Challenges
- • Handling noisy and incomplete financial data
- • Feature engineering for time-series forecasting
- • Avoiding model overfitting in volatile markets
The Solution
- • Applied robust data cleaning & Z-score normalization
- • Implemented LSTM with specialized dropout layers
- • Utilized walk-forward validation & backtesting
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Impact & Results
18% accuracy lift vs baseline models
Significant reduction in MAE/RMSE metrics
End-to-end automated deployment pipeline