The title of this blog is accurate
There are indeed some caveats / disadvantages to automated machine learning.
This blog was motivated by a question in my University of Oxford class effectively asking:
Will automated machine learning take over all the data scientists’ tasks?
If you listen to the prevailing view in the industry, automated machine learning will be like the 1950s labour saving devices – it would give us lots of leisure time – with no ‘cost’ on our side.
Here are my views
We need to break this question down a bit:
So, what is automated machine learning?
When we refer to the term ‘automated machine learning’ we are speaking of automating specific tasks in the data science pipeline
These include:
At the higher end, there are other elements that can be automated. These include:
So, what are the disadvantages of this approach?
I am old enough to know Case tools.
In the case tools world, Managers fantasised of ‘building the system at the push of a button’ – sans developers!
Fast forward a few years, the managers are gone and the developers are there and even more valuable ..
But new tools have been developed to make things easy for the developers.
So, coming back to Automated machine learning, here are the caveats you should consider to take a balanced view
Image source: thebestofhealth.co.uk
1950s labour saving devices life of leisure somehow that did not quite happen
Posted 1 March 2021
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