In this talk, Bin Yu, professor at UC Berkley, discusses the intertwining importance and connections of three principles of data science.

The three principles will be demonstrated in the context of two neuroscience projects and through analytical connections. In particular, the first project adds stability to predictive models used for reconstruction of movies from fMRI brain signals to gain interpretability of the predictive models.

The second project employs predictive transfer learning and stable (manifold) deep dream images to characterize the difficult V4 neurons in primate vision cortex. Our results lend support, to a certain extent, to the resemblance to a primate brain of Convolutional Neural Networks (CNNs).

Veljko Vasic explains how Azure SQL Database uses built-in intelligence to continuously monitors database usage so that it can detect disruptive events that cause poor performance.

Once detected, a detailed analysis is performed generating a diagnostic log with an intelligent assessment of the issue, which consists of a root cause analysis of the database performance issue and recommendations for performance improvements where possible (i.e., intelligent insights).

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