The ML workflow
To develop and manage a production-ready model, you must work through the following stages:
Train an ML model on your data:
Deploy your trained model.
Send prediction requests to your model:
Monitor the predictions on an ongoing basis.
These stages are iterative. You may need to reevaluate and go back to a previous step at any point in the process.
MORE LIKE THIS
How to build a data science and machine learning roadmap in 2022
Machine Learning-based Type Auto-completion for Python – The Blog of Amir Mir