So I have been playing those fun Facebook games
for a while where they say you'll get married in this year or you'll have this many kids or this much money bla bla. But noboady gives you the reason why? I think these are pretty random. So thought of building a fun game using Machine Learning
, and provide some Data Driven results.
- I have collected data of richest persons in 100+ different fields from more than 100 countries. I have used
BeautifulSoup
to scrape therichest.com. - After collecting the data done some data cleaning and feature engineering on raw data.
- Fitted multiple regression model and used hyper parameter tuning to get the best result.
- Saved the model in a
.pkl
file and. - Later used the same model in the
flask app
and for frontend usedHTML, CSS
andBootstrap
. - Deployed the whole project on ``Heroku
and used
Google Analytics` for tracking users.
To run the app you need to download this repository along with the required libraries. and you have to the
app.py
file.
after running
app.py
open http://127.0.0.1:5000
Personal Finance
│
|---- Data
| |-- preprocessed_df.csv
| |-- Rich.csv
|
|---- results
| |-- desktop_home.png
| |-- desktop_prediction.png
| |-- mobile_home.png
| |-- mobile_prediction.png
|
|---- scraper
| |-- webscraper.py
|
|---- static
| |-- images
| |
|
| |-- styles
| | |-- index.css
| | |-- prediction.css
|
|---- templates
| | |-- index.html
| | |-- layout.html
| | |-- prediction.html
|
|
|---- app.py
|---- LICENSE
|---- model_training.ipynb
|---- markdown.py
|---- random_forest_regression_model.pkl
|---- random_forest_regression_model.sav
|---- README.md
|---- requirements.txt
- python library - numpy, pandas, seaborn, matplotlib, flask, plotly, sklearn, joblib, bs4
- version control - git
- backend - flask
- concept - Machine Learning
- IDE - Vs code
- Application Deployment - local host
- Code Repository - GitHub