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Stock price prediction using Bidirectional LSTM and sentiment analysis

License: MIT License

Python 29.23% CSS 2.23% JavaScript 42.40% HTML 26.14%

stock-price-forecasting-using-artificial-intelligence's Introduction


New approach for stock market prediction using Artificial Intelligence

Techniques used

Bidirectional LSTM on historical data

Sentiment analysis with news and twitter feeds

Django + Angular JS combination for web app


Python packages

LAMP installed







JS packages


Angular JS

Chart JS

How to run

first terminal

git clone [email protected]:koriavinash1/FIN_ishers.git
cd Stock-Price-Forecasting-Using-Artificial-Intelligence/StockNest
python makemigrations
python migrate
python runserver

second ternimal

cd Stock-Price-Forecasting-Using-Artificial-Intelligence/StockNest
celery -A StockNest worker -l info

First steps

  • data collection: Once server is on, navigate to localhost:8000/stocksadmin download all the required data

  • train model from same stocksadmin page

  • once model is trained, you can use product from localhost:8000/index paage

DL model information

  • DL model information can be found in FIN_ishers/StockNest/stock_backend

  • Django restapis can be found from all apps/ script


temp1 temp2

Observed RMSE < 0.05 on test data


If any comments or information required, pull requests/issues are Welcomed....


stock-price-forecasting-using-artificial-intelligence's People

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