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Sales-Forecast-Prediction-using-Angular-and-Flask Sales forecasting app using Angular, Flask, and a RandomForestRegressor ML model. Upload sales data, set parameters, and visualize forecasts on a responsive dashboard. API handles requests for training and prediction. Optimized with hyperparameter tuning for best performance.

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Sanjaykumaran10/Sales-Forecast-App-using-Anguar-and-Flask

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Sales Forecast App Using Angular And Flask

This project was generated with Angular CLI version 15.1.4.

Development server

Run ng serve for a dev server. Navigate to http://localhost:4200/. The application will automatically reload if you change any of the source files.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via a platform of your choice. To use this command, you need to first add a package that implements end-to-end testing capabilities.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI Overview and Command Reference page.

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Sales-Forecast-Prediction-using-Angular-and-Flask Sales forecasting app using Angular, Flask, and a RandomForestRegressor ML model. Upload sales data, set parameters, and visualize forecasts on a responsive dashboard. API handles requests for training and prediction. Optimized with hyperparameter tuning for best performance.

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