Cleaning the data (the process of identifying and removing (or correcting) inaccurate records from a dataset, table, or database and refers to recognizing unfinished, unreliable, inaccurate, or non-relevant parts of the data and then restoring, remodeling, or removing the dirty or crude data) as we found the data of some important records are wrong, user could enter anything without validation. Thus we need to clear the data to make them useful for our model since machine learning from wrong data will cause predicting wrong results.
To apply a set of scripts to detect these cases and correct data. These scripts would be applied on the database directly. By apply this, it should enable the current machine learning settings to scrap the correct data into correct table in our standard WHR Solution Resume template.