In this advanced quest, learners will dive deep into the world of deep learning applied to computer vision using PyTorch. Participants will explore complex architectures such as Convolutional Neural Networks (CNNs), Residual Networks (ResNets), and Generative Adversarial Networks (GANs). The quest will guide learners through the intricacies of data preprocessing, model training, and optimization techniques to improve accuracy and performance. Additionally, learners will work on hands-on projects, including image classification, object detection, and image generation, ensuring they gain practical experience. By the end of this quest, participants will have a robust understanding of the state-of-the-art methods in computer vision and the skills to implement them effectively using PyTorch.
