#Creating the Model

1. Understand Business Problem
- Create a model to predict the salary of a new hire based on the historic data with test_score, interview_score and experience (I/P).
 HR should be able to enter the details in a form and should receive predicted salary from the model.
2. Data Collection 
3. Data Exploration - info(),describe()
4. Data Cleaning
5. Data Wrangling
6. Modelling
   
1. Train-Test Split
 2. Creating model
 3. Training model with Train Data (X_Train and Y_Train.
7. Evaluate the model with Test Data(X_Test)
 RMSE and R2
8. Dumping the model - Save the model to a local folder 


#Creating the Flask Application

1. Load the model
2. Creating the routes /Index - For HTML page /predict For calling the model with predicted data
3. Test /predict endpoint from the postman POST request
4. Creating the HTML Page and calling /predict route