Akademik Veri Yönetim Sistemi
This course aims to give background knowledge on several topics related to deep learning and provide a laboratory environment for practical applications. Backpropagation convolutional neural networks, generative adversarial networks, energy-based learning and optimization techniques are some of the core topics that will be covered through the lectures. The course aims to balance theory and practice in that it will involve students implementing all of the described algorithms, testing those algorithms under several domains and accessing GPU clouds during laboratory sessions to program examples using Torch.