Stock Price Prediction using LSTM

This project uses LSTM (Long Short-Term Memory) to predict future stock prices based on historical data. The model is trained on stock prices (e.g., Google) to forecast future values.

Key Features: Data Preprocessing: Clean, scale, and split data into training and testing sets. LSTM Model: Build and train an LSTM model to forecast stock prices. Prediction & Visualization: Compare predicted prices with actual values and visualize the results.

Technologies: Python TensorFlow/Keras Matplotlib/Seaborn scikit-learn This project demonstrates time series forecasting using LSTM for stock price prediction.