kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
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
Ensemble prediction combines outputs from ARIMA, LSTM, and Linear Regression models to improve forecast accuracy, with sentiment scores from Twitter API weighted into the final buy/sell recommendation logic. The backend integrates Django with Keras/TensorFlow for model training and inference, while WordPress handles admin dashboards and user management through a custom plugin architecture. Real-time stock data is fetched via financial APIs (Yahoo Finance or similar), processed through pandas/NumPy pipelines, and served to Flask-based prediction endpoints that output 7-day forecasts with confidence metrics.
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Language
Python
License
MIT
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Last pushed
Feb 19, 2024
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