The aim of this project is to provide users help to avoid losses and invest wisely.This project has been developed as a POC.
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A brief explaination about the methodlogy used:-
- The model has been trained on the publically available stock price data of Banks .
- The model uses Linear regression to predict the Highest and Lowest Price of the stock.
- After the data is collected, the data is then pre-processed for the model.
- The model then predicts the outcome as an arrray of two elements which are numerical values.
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Task performed:- The classical Machine Learning task like data exploration,feature engineering,model buiding, model testing,Hyperparameters tuning etc.
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Deployment:- The model has been deployed locally using Tkinter as GUI for Desktop App while MySQL is used as databse to store the predicted values .
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Model:- Model used here is Linear Regression.
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Accuracy:- The model has a r2 score close to 90.00%. -IDE:- Spyder
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Demo Video:-
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Untitled.1.mp4