What are the disadvantages of Azure's ML vs a pure code approach (R/SKlearn)
I learned the Azure ML platform after scikit-learn (Python) and caret (R).

Advantages:


Low or no coding involved. It is more like Orange in that you set up the ML exercise as a large process flow. It is easier for non-technical people to get started with.
Easy to convert to production-ready. You click a button and it deploys a web-service that you could send to a programmer to use. In Python, you would need to add another library and in R it is even dicier.


Disadvantages:


Fewer algorithms (e.g. no XGBoost) and other transformations (e.g. NLP) built-in. You can of course reference Python and R to do this, but that is much tougher than using the GUI. If you can figure out how to call Python/R from within Azure ML, you likely can do it on your own.
Price.