Employee Salary Prediction

Problem Statement:

In this competitive world everyone has a higher goals and expectation for their dream jobs. For an employer it is challenging work to predict justified salary for an employee. And he cannot provide randomly their expected salary to everyone .Now the question is how to choose right salary for an employee????

Solution:

Designing a system(website) that will take some inputs (employee details like : experience, qualifications, skills, test score, interview score etc. ) and automatically decide/predict the salary of an employee.

Objective:

To design a system (website) that will predict the salary of an employee by using regression machine learning algorith like:linear , ridge , lasso, elastic net,decision tree regressor, random forest regressor.to determine the best fit model for the deployment.

Requirements:

To run this project, you will need to download the following :

IDE: jupyternotebook

python version : 3.9.12

libraries : mentioned in requirements.txt

pycharm version : 23.1.1

Task:

• Import Required library
• Importing Dataset
• Data Understanding
• Describing Dataset
• Cleaning Dataset
• Feature Tansformation
• Splitting Dataset into Train and Test
• Model Building |Linear Regression|
• Model Evaluation

Conclusion :

Sucessfully built an employee salary prediction model that predicts the salary of an employee with an accuracy of 87%.