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- Introduced Machine Learning for Life Expectancy and Wealth Analysis.
- Proper Financila Planning for Retirement and Old Age.
- Visual and Detailed Displays with Analysis.
- Charts and Graphs for enhanced calculations
- Management Flow.
- Realtime Cash Flows, Statements, Investments and Retirement monetary values
After it receives certain necessary inputs from user (i.e. current age, salary, health related info, etc), it will show all the required information including graphs and charts for better view and financial controls. It also uses Machine Learning to improve for more better investments.
Including solutions that support retirement planning for longer lives or protect against financial abuse.
It is a Web Based Project that requires a browser and internet connection to be operable.
Some Examples -
1. Savings
2. Stock Investments
3. Savings and Investments Analysis for Old Age.
4. To have enough wealth for secure retirement and still have your pleasures during old age.
On front end -
1. Receives inputs through a form from user.
2. Calculates and Displays the data and other information including visual charts.
3. Realtime data analysis calculator.
On back end -
1. Machine Learning Model that predicts Life Expectancy from certain parameters and also total wealth calculation.
2. Realtime Calculation for Realtime Analysis Calculator.
For video demostration refer to the YouTube link here.
- JavaScript/TypeScript
- Python 3
- C#
- Angular 9
- BootStrap 4.6
- Chart.js 3.1
- ASP .NET CORE WEB API
Clone the repo
$ git clone https://github.com/raj713335/INVESTOPIA.git
$ cd INVESTOPIA
Run INVESTOPIA_TSQL.sql script present in the project root diectory
From Folder INVESTOPIA/Financial Tools for Longevity/FinancialToolsforongevity.ServiceLayer
- Install Python 3.7.3 and its required Packages like tensorflow etc.
$ pip install numpy
$ pip install scipy
$ pip install scikit-learn
$ pip install matplotlib
$ pip install pandas
$ pip install fastapi
$ pip install uvicorn
$ pip install gunicorn==19.9.0
$ pip install uvloop
$ pip install httptools
- Run the app
$ python INVESTOPIA/ML Components/app.pyThis project was generated with Angular CLI version 9.0.7.
Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.
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.
Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the -prod flag for a production build.
Run ng test to execute the unit tests via Karma.
Run ng e2e to execute the end-to-end tests via Protractor.
To get more help on the Angular CLI use ng help or go check out the Angular CLI README.
Add the node_modules Folder inside AGEING-BETTER-WITH-ICTs/LongevityAPP Folder
Angular Installation Commands
$ npm install chart.js
$ npm install jquery
$ npm install bootstrap font-awesome
$ npm install bootstrap@next
$ npm install ngx-captcha
$ npm install --save igniteui-angular-core
$ npm install --save igniteui-angular-charts
Run the App
$ ng serve -o