predictos's Introduction

Predictos

Predict your potential networth using Ai

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 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 Data Driven results.

Approach :

I have collected data of top 100 richest persons in different fields. 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 .sav file and.
later used the same model in the flask app

How to run?

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

Document Structure

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

Technologies used :

python library - numpy, pandas, seaborn, matplotlib, flask, plotly, sklearn, joblib, bs4
version control - git
backend - flask
concept - Machine Learning