Interactive demo of an LSTM-based deep learning model for time series forecasting. Predicts stock prices with 94% R² score using historical data and technical indicators.
R² Accuracy Score
Mean Absolute Error
Sequence Length
Inference Time
Traditional stock analysis relies on manual technical indicator interpretation and lagging signals, often missing short-term price movements. Traders need predictive insights that account for complex temporal patterns across multiple indicators simultaneously.
Built a 3-layer LSTM neural network trained on 60-day sequences with 15+ technical indicators. The model captures long-term dependencies and momentum patterns, providing actionable forecasts with confidence intervals for risk management.
Select parameters to generate stock price forecast