Application to predict salary of an employee based on basic information like experience, country, education etc. This application uses Knowledge of data provided by StackOverlow which comes from a servey it conducts every year. Stack Overflow annual developer survey include over 70,000 responses to curate the whole data. for csv file please refer to https://insights.stackoverflow.com/survey.

• Try Out the app

https://rht174-salary-prediction-app-streamlit-app-rqsiqe.streamlitapp.com/

This is how end application would look like :

Since desired output is continous we can use any variation of regression model. i have compared 3 models linear regression, Random Forest and Decision Tree in which i found decision tree worked the best for the type of data we have.

1. Installing all the dependencies
2. Pre-processing of the data

   • Droping irrelevent Columns

   • Dealing with NaN values and null values

   • Removing the outliers Our Raw data with outliers

     Our data after removing outliers

   • Encoding the categorical labels with scikit-learn lib.

3. Trial of 3 different models (linear reg, random forest, decision tree)
4. Evaluating with model performing well
5. Making web application with Streamlit

1. Numpy
2. Pandas
3. Matplotlib
4. scikit-learn
5. streamlit