Life cycle of machine learning:
- Acquisition . Collect the data
- Prepare - Data Cleaning and Quality
- Process- Run Machine Tools
- Report- Present the Results
You must come to accept that data will need to be cleaned and checked for quality before any processing can take place. These processes occur during the prepare phase.
The processing phase is where the work gets done. The machine learning routines that you have created perform this phase.
Finally, the results are presented. Reporting can happen in a variety of ways, such as reinvesting the data back into a data store or reporting the results as a spreadsheet or report.