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Many important questions in development economics remain unanswered, partly because the data required to address them is encoded in high-dimensional data structures such as images. This course begins with an overview of novel data sources for development economists and then offers a comprehensive introduction to image processing techniques and specialised neural network models for analysing image data. While grounded in theory and mathematical formalisation, the course emphasises intuitive understanding and practical implementation using Python. By the end of the course, students will be able to leverage a variety of data sources for empirical work, including satellite and street-view images, historical maps, and documents, for tasks such as regression, classification, localisation and segmentation.

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