Course Detail
Units:
3.0
Course Components:
Lecture
Description
Foundations and application of deep neural networks for vision related tasks including image classification, object detection, segmentation, image generation and vision/language multimodal models. Basics of machine learning for neural networks: Learning with backpropagation, evaluating models, hyper-parameter selection. Neural network architectures from a historical perspective to modern models including convolutional neural networks and transformers.