MLOps
The problem with is every step - cleaning, imputation, encoding, feature engineering, etc, is done separately so if a new test sample is given, one cannot directly make a prediction and will have to carry out every step all over again. To solve this, I am going to create a 'preprocessor' class with a transform method that does everything I have done until now and make a pipeline with this preprocessor as the first step and the trained model clf as the second step.