Neural Networks exam in a week!
Today's AA exam went much better than expected, given how little I studied for it. That kinda thing totally incentivises the wrong kind of behaviour.
What to do. I'll start with the (overdue) assignments and try to understand as much of the mind-boggling math as I can.
And perhaps some day, I'd be able to do something cool like these guys:
Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries—Nigeria, Tanzania, Uganda, Malawi, and Rwanda—we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.