Microsoft Stock Price Prediction

Project Overview

This project contains code and resources for predicting Microsoft stock prices using TensorFlow and LSTM (Long Short-Term Memory) networks. The goal is to build a model that can accurately forecast future stock prices based on historical data.

DataSet

The dataset used for training and testing the model is historical Microsoft stock price data. The dataset should be provided as a CSV file, containing the following columns:

• Date: The date of the stock price record.

• Open: The opening price of the stock on that day.

• High: The highest price of the stock on that day.

• Low: The lowest price of the stock on that day.

• Close: The closing price of the stock on that day.

• Volume: The trading volume of the stock on that day.

Tech Used

• Python

• TensorFlow

• Pandas

• NumPy

• Matplotlib

Result

After running the code, the predicted Microsoft stock prices for the test set and a visualization of the predicted prices compared to the actual prices is obtained.

Future Aspects

With the help of LSTM Model a web app will be made using Streamlit framework which will show live prediction of stocks of Microsoft.

Acknowledgments

• The code in this repository is based on the concepts and techniques from the field of deep learning and time series analysis.