Is AutoML a Panacea for Data Science Talent Shortages?

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The talent shortage in data science is a significant challenge for many organizations. Automated machine learning (AutoML) has been touted as a solution to this problem. At Data Science Connect, we explore whether AutoML can really ease the data science talent gap.

Discover how AutoML is enabling businesses to leverage their existing data resources without requiring specialized data scientists. Learn about the limitations of the technology and how it may impact data science in the future. Explore real-world examples of how companies are using AutoML to bridge the talent gap in data science, and learn from their experiences.

Join the conversation on whether AutoML is a panacea for data science talent shortages, and stay up-to-date on the latest trends and best practices in artificial intelligence and machine learning at Data Science Connect.

Rajkumar Bondugula

PhD | Chief AI Scientist

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