Learn to implement semantic image segmentation using U-NET architecture from scratch in this comprehensive 52-minute PyTorch tutorial. Dive deep into the U-Net implementation, dataset preparation, training process, and utility functions. Follow along as the instructor builds a complete image segmentation pipeline using the Carvana Image Masking Challenge dataset. Gain hands-on experience in creating custom datasets, designing the U-Net architecture, setting up training loops, and evaluating model performance. Perfect for deep learning enthusiasts looking to master advanced computer vision techniques and understand the intricacies of image segmentation tasks.