{"id":1079,"date":"2023-11-13T13:38:00","date_gmt":"2023-11-13T17:38:00","guid":{"rendered":"https:\/\/ccdhhn.ca\/workshop\/deep-learning-for-humanists-2\/"},"modified":"2023-11-15T23:26:02","modified_gmt":"2023-11-16T03:26:02","slug":"deep-learning-for-humanists-2","status":"publish","type":"tribe_events","link":"https:\/\/ccdhhn.ca\/fr\/workshop\/deep-learning-for-humanists-2\/","title":{"rendered":"Deep Learning for Humanists"},"content":{"rendered":"
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\n\t\t\n\t\t\tjuin 3, 2024\t\t<\/span>\n\n\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t – \t\t\t\t<\/span>\n\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\tjuin 7, 2024\t\t\t\t<\/span>\n\n\t\t\t\t\n\t\t\t\n\t\t\t\t\t\t<\/p>\n<\/div>\n\n\n

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Format <\/h3>\n\tin person\/face-\u00e0-face<\/div>\n\n\n

This hands-on course will introduce neural networks, image preprocessing, and deep learning models for those who wish to explore deep learning for the digital humanities. This course will first focus on learning activation functions, loss functions, and gradient descent, then explore image processing and deep learning models. After that, we will train GANs (Generative Adversarial Networks) and cGANs (conditional Generative Adversarial Networks) models to colorize black-and-white images. Throughout this course, participants will be able to create their own datasets for deep learning then run deep learning models with them.<\/p>\n\n\t

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