Why do Businesses need to leverage AutoML today, more than ever?


Most of the business leaders claim that the lack of qualified personnel with skills in artificial intelligence (AI) has been a major barrier to its implementation across businesses. With more and more companies choosing to leverage artificial intelligence and its applications like machine learning, deep learning, and more, the knowledge gap can prove a costly affair. While data scientists are helping to build AI applications for data mining, analyzing, filtering the raw data, along with selecting an algorithm to train machine learning models, their roles are diversifying in recent years. Coupled with the acute talent shortage, as the job positions for data scientists are rapidly increasing, companies face the risk of trailing behind in the race of digital transformations. Therefore, business leaders are looking to automate some of the roles and responsibilities of a data scientist.

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