https://github.com/rupashi03/stock-price-prediction-lstm

This project predicts the prices of five selected stocks using LSTM model, leveraging historical data and time-series analysis techniques.
https://github.com/rupashi03/stock-price-prediction-lstm

deep-learning finance financial-forecasting lstm predictive-analytics sequential-models stock-price-prediction time-series

Last synced: 10 days ago
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This project predicts the prices of five selected stocks using LSTM model, leveraging historical data and time-series analysis techniques.

• Host: GitHub
• URL: https://github.com/rupashi03/stock-price-prediction-lstm
• Owner: rupashi03
• Created: 2024-11-09T17:10:13.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-22T14:52:54.000Z (3 months ago)
• Last Synced: 2024-12-11T03:24:31.434Z (2 months ago)
• Topics: deep-learning, finance, financial-forecasting, lstm, predictive-analytics, sequential-models, stock-price-prediction, time-series
• Language: Jupyter Notebook
• Homepage:
• Size: 141 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 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)