As a student of physics and astronomy, I spent a significant proportion of my time dealing with data from measurements and simulations, with the goal of deriving scientific value by analyzing, visualizing, and modeling the data. With a background as a programmer, I quickly learned to use my programming skills as an important aspect of working with data. When I was first introduced to the world of machine learning, it showed not only great potential as a new tool in the data toolbox, but also a beautiful combination of the two fields that interested me the most: data science and programming.

Machine learning became an important part of my research in the physical sciences and led me to the UC Berkeley astronomy department, where statisticians, ...

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