Stock-Market-Prediction-Web-App-using-Machine-Learning

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall.

System Description and Functions

Demo Video: Screenshots:

Admin Creds: Username: admin Email Address: stockpredictorapp@gmail.com Password: Samplepass@123

There are two roles in the system: Admin and User. Users can:

Admin can:

Built With

Installation

1. Install XAMPP server
2. Download wordpress zip folder from this link.
3. Extract the downloaded zip into htdocs folder of XAMPP.
4. Open the wp-config.php file from the extracted folder and add your phpmyadmin username and password.
5. Go to phpmyadmin, create a new database called wordpress.
6. Select this database, go to Operations tab and Import the wordpress.sql file into this created databse.
7. Clone the repo, cd into it
8. Run pip install -r requirements.txt
9. Run python main.py to start server.
10. Go to localhost/wordpress to access the app.

Find more screenshots in the screenshots folder Or click here

Authors

Kaushik Jadhav

Links

• Issue tracker
• Source code