This repository presents a deep learning approach to predicting Google stock prices using Long Short-Term Memory (LSTM) models. Leveraging the power of recurrent neural networks, specifically LSTM architecture, this project aims to forecast future stock prices based on historical data. The LSTM models learn from patterns and dependencies in the historical stock data to make predictions, providing insights into potential market trends. The project includes data preprocessing, model training, and evaluation, offering a comprehensive solution for predicting Google stock prices in the financial market.