Currently, running data science and machine learning projects are strictly the prerogatives of data scientists who need to work with cleaning the data and performing exploratory analysis before identifying different models, running them on by one, performing parameter tuning and dynamically updating the prediction log based on what the various models are telling.
Additionally, with the shortage of data scientists in the industry, and even more, lack of data science experts who carry strong functional and industry understanding, it results in data science projects often failing to integrate the desired levels of functional knowledge to make accurate and powerful predictions.
AutoML can be by anyone – from data scientists, software engineers, business analysts and functional leaders to run several different machine learning models at the same time on the data set to perform both unsupervised clustering exercises as well as supervised predictive models, in order to dynamically produce the best performing model.
It is helping them to become more innovative, do more customer-centric use cases, collaborate with partners, create a business impact and give the power to run advanced machine learning applications to anyone within the organization who would benefit from it.
AutoML gives the power and effectiveness of executing advanced models to everyone – from data scientists, business analysts, analytics professionals as well as functional leaders and managers, software engineers etc.