kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Seven-day stock forecasts stitched from ARIMA, LSTM, and tweets
This web app ensembles ARIMA, LSTM, and linear regression with live tweet sentiment to forecast whether NASDAQ or NSE stocks will rise or fall over the next seven days.
Not currently ranked — collecting fresh signals.
star history
What it does
The app accepts a ticker from NASDAQ or NSE and forecasts its price for the next seven days using three distinct models: ARIMA, LSTM, and linear regression. It then applies Twitter sentiment analysis and blends those opinions with the numeric predictions to issue a directional recommendation—rise or fall. The surrounding application includes user registration, real-time price checks, news, a currency converter, and an admin dashboard.
The interesting bit
The architecture is an odd marriage of Flask and WordPress, and the README openly notes that API keys are baked into the code. Rather than picking one modeling approach, it runs all three algorithms side by side and layers social-media sentiment on top, treating the market as part math and part mood.
Key highlights
- Forecasts 7-day prices for any NASDAQ or NSE ticker using ARIMA, LSTM, and linear regression
- Combines predicted prices with Twitter sentiment analysis to recommend direction
- Bundles auxiliary tools: real-time quotes, stock news, a currency converter, and user profile management
- Supports Admin and User roles integrated with a WordPress management layer
Caveats
- API keys and admin credentials are exposed directly in the source code and README
- The “Built With” badges list Django, React, and Node.js, which contradicts the stated Flask-and-WordPress stack, so the actual technology boundaries are unclear
- Deployment requires a local XAMPP/PHPMyAdmin/WordPress stack rather than a standalone Python service
Verdict
This is essentially glue code—kindly assembled—connecting stock data, tweet sentiment, and three forecasting models behind a WordPress-and-Flask facade. Students looking for a full-stack ML demo may find it instructive; anyone expecting production security or clean architecture should steer clear.
Frequently asked
- What is kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis?
- This web app ensembles ARIMA, LSTM, and linear regression with live tweet sentiment to forecast whether NASDAQ or NSE stocks will rise or fall over the next seven days.
- Is Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis open source?
- Yes — kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis is open source, released under the MIT license.
- What language is Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis written in?
- kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis is primarily written in Python.
- How popular is Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis?
- kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis has 891 stars on GitHub.
- Where can I find Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis?
- kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis is on GitHub at https://github.com/kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis.