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Opinion
Is AutoML ready for Business?
Do (will) we still need Data Scientists?
AutoML tools have been gaining traction for the last couple of years, both due to technological advancements and their potential to be leveraged by ‘Citizen Data Scientists’. Citizen Data Science, is an interesting (often controversial) aspect of Data Science (DS) that aims to automate the design of Machine Learning (ML)/Deep Learning (DL) models, making it more accessible to people without the specialized skills of a Data Scientist.
In this article, we will try to understand AutoML, its promise, what is possible today?, where AutoML fails (today)?, is it meant only for Citizen Data Scientists, or does it hold some value for skilled Data Scientists as well?
AutoML Internals
Let us start with a very high-level primer on Machine Learning (ML). Most of today’s ML models are supervised and applied on a prediction/classification task. Given a dataset, the Data Scientist has to go through a laborious process called feature extraction and the model’s accuracy depends entirely upon the Data Scientist’s ability to pick the right feature set. For simplicity, each…