Stock Price Prediction

This repository contains a project for predicting stock prices using Recurrent Neural Networks (RNN), specifically Long Short-Term Memory (LSTM) networks, with Python, scikit-learn, Keras, NumPy, Pandas, and Matplotlib.

Overview

The goal of this project is to predict future stock prices based on historical data. The model uses RNNs, particularly LSTM networks, to capture temporal dependencies in the stock price data.

Features

• Recurrent Neural Networks: Utilizes LSTM networks for time series prediction.
• Data Processing: Uses NumPy and Pandas for data manipulation.
• Visualization: Matplotlib for visualizing stock price trends.
• Model Evaluation: Implements scikit-learn for performance metrics.