Demystifying Deep Learning: An Intuitive Introduction to Neural Networks (Part 1)

This two-part workshop goes from a gentle introduction to key concepts in deep learning to the mechanics of advanced architectures used in the cutting edge of research. In Part 1, we will cover the core building blocks of neural networks models, and gain an understanding of the key intuitions behind using neural networks to model data.

The format is a lecture with an accompanying take-home coding notebook to provide participants with both the theoretical and technical tools necessary to begin research in this area.

The workshops are designed with quantitative social science scholars in mind. Explanations will be made with reference to existing techniques and approaches in quantitative social science research in order to help scholars link concepts and practices in the two fields.

The workshop will be provided in-person and over Zoom. Please indicate whether you intend to attend in-person or online in your RSVP.

The instructor, Dr Musashi Jacobs-Harukawa, is a postdoctoral research associate at the Data-Driven Social Science Initiative. He received his doctorate at the University of Oxford, where he wrote his dissertation on applications of machine learning and natural language processing to studying political campaigns.