README.md

Stock-Price-Prediction-LSTM-ARIMA

This project uses Long Short-Term Memory (LSTM) to predict the stock prices of five major companies: Microsoft, Tesla, Apple, Tata Beverages, and Facebook. The project demonstrates the use of time series analysis to predict future stock prices based on historical data.

The results from LSTM is evaluated, its predictive performance measured.

Key Features

LSTM Model: A deep learning-based model for predicting stock prices using historical data.

Performance Comparison: To show that LSTM is more accurate than historical models for time series analysis.

Technologies Used

Python

TensorFlow/Keras (for LSTM model)

Pandas (for data manipulation)

NumPy (for numerical operations)

Matplotlib/Plotly (for visualizations)

Flask (for dashboard)