Salary Prediction Based on work experience ML Web App. The purpose of this project is to use data transformation and machine learning to create a model that will predict a salary when given years of experience, job type. The purpose of this project is to use data transformation and machine learning to create a model that will predict a salary when given years of experience, job type.

Data The data for this model is fairly simplified as it has very few missing pieces. The raw data consists of a training dataset with the features listed above and their corresponding salaries.

Information Used To Predict Salaries Years Experience: How many years of experience .

This model can be used as a guide when determining salaries since it shows reasonable predictions when given information on years of experience.

Methods Used

1. Data Analysis and Visualization
2. Linear Regression
3. Polynomial Transformation
4. Ridge Regression
5. Random Forest

Technologies/Libraries Used

1. Python 3
2. Pandas
3. NumPy
4. Seaborn
5. Scikit-learn
6. Matplotlib
7. SciPy
8. Jupyter

Data

The data for this model is fairly simplified as it has very few missing pieces. The raw data consists of a training dataset with the features listed above and their corresponding salaries. Twenty percent of this training dataset was split into a test dataset with corresponding salaries.

There is also a testing dataset that does not have any salary information available and was used as a substitute for real-world data.

Information Used To Predict Salaries

1. Years Experience: How many years of experience

Overview

1. This is project predicts the salary of the employee based on the experience.

Model Training :-

    model.py trains and saves the model to the disk.
    model.pkb the pickle model

Run App :-
    app.py contains all the requiered for flask and to manage APIs.

Procedure
Open command Prompt and go to given directory and then run python app.py

Download Link