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Machine Learning Model trained using Lasso with a HTML/CSS UI built on top of it.

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Salary Estimation Machine Learning Model & Webapp

This repository contains a Machine Learning model and a web application for predicting salaries based on various factors such as age, years of experience, gender, education, and position.

Project Overview

The Salary Prediction web application is a machine learning-based tool that predicts the salary of individuals based on various features such as age, gender, education, years of experience, and job position. It utilizes a pre-trained machine learning model to make accurate salary estimates
The project is implemented with a modular and scalable approach, allowing for easy maintenance and future enhancements.
The model was trained using Lasso algorithm.
The web application has a user-friendly interface where users can input their information and receive an estimated salary as the output. The application makes use of JavaScript for client-side functionality
And server side was built using Flask Framework (python)

ScreenShots

Screenshot (75) Screenshot (76) Screenshot (77) Screenshot (78) ezgif com-gif-maker

Installation

before running the app you have to local server. 1.To start it, go to ./server and pass 'python server.py' in cmd
2.You'll need to change host urls in code to your host urls (will be shown in cmd after running the server)
3.Go to ./client and open app.html
4.FIll out the feilds and click predict salary button to get the result

Technologies Used

Python
scikit-learn (Python machine learning library)
Pandas
Numpy
Flask (Python web framework)
HTML
CSS
JavaScript
jQuery (JavaScript library)

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Machine Learning Model trained using Lasso with a HTML/CSS UI built on top of it.

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