Author: Streamline

IntroductionIn the fast-paced world of technology, change is the only constant. Among the latest breakthroughs in artificial intelligence (AI) and machine learning (ML), Automated Machine Learning, or AutoML, is turning heads, and for good reason. AutoML is transforming the way models are built, trained, and deployed, significantly reducing the need for deep technical expertise in traditional data science workflows. But what does this mean for the roles and responsibilities of data scientists? Is this the beginning of a fully automated data science era, or is it an evolution of the role itself?Let us dive into the rise of AutoML and…