- Reading the data
- Checking for duplicated values and removing the records if it presents in dataset
- Checking for null values or missing values
- Checking for outliers by using the boxplot
- Imputing the IQR Range values
- Replacing the outliers with upper bound ,lower bound
- Deviding the data set into train set and test set
- Training the algorithm with train data and test performance
- Testing the model with test data and measure the metrics
- Creating model using pickle module
- Create application using streaamlit