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
Wordpress file has been moved from the repository due to exceeding quota of Github LFS. Download it now from here
screenshots - Screenshots of Web App static - static files of flask app: css, images, js, etc. templates - html files Tweets.py - structure of Tweets for sentiment Analysis constants.py - config file for app with Twitter API keys and other details main.py - main machine learning module
- Wordpress
- Flask
- Tensorflow
- Keras
- Yahoo Finance
- Alphavantage
- Scikit-Learn
- Tweepy
- Python
- PHP
- CSS
- HTML
- Javascript
- Download and install Wordpress from https://wordpress.org/download/
- Once wordpress is installed, install All In One WP Migration Plugin on Wordpress
- Download my wordpress website file "localhost-wordpress-20200313-074610-uxz1wx (1).wpress" from here
- Once installed, go to the plugin and import the file "localhost-wordpress-20200313-074610-uxz1wx (1).wpress"
- Go to command prompt, change directory to directory of repository and type pip install -r requirements.txt
- To run app, type in command prompt, python main.py
- Open your web browser and go to http://localhost/wordpress to access the web app