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As machine learning evolves, we need to update the definition of ‘data scientist’

In the early days of machine learning, hiring good statisticians was the key challenge for AI projects. Now, machine learning has evolved from its early focus on statistics to more emphasis on computation.

As the process of building algorithms has become simpler and the applications for AI technology have grown, human resources professionals in AI face a new challenge. Not only are data scientists in short supply, but what makes a successful data scientist has changed. Divergence between statistical models and neural networks As recently as six years ago, there were minimal differences between statistical models (usually logistic regressions) and neural networks.

Source: venturebeat.com
Author: Bernardo Lustosa

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