YoVDO

PyTorch Image Segmentation Tutorial with U-NET - Everything From Scratch

Offered By: Aladdin Persson via YouTube

Tags

PyTorch Courses Deep Learning Courses Computer Vision Courses Image Segmentation Courses Model Training Courses Semantic Segmentation Courses U-Net Courses

Course Description

Overview

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.

Syllabus

- Introduction
- Model from scratch
- Dataset from scratch
- Training from scratch
- Utils almost from scratch
- Evaluation and Ending


Taught by

Aladdin Persson

Related Courses

PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course
freeCodeCamp The Role of Data and Models for Deep-Learning Based Image Reconstruction
Institute for Pure & Applied Mathematics (IPAM) via YouTube Creating an Animal Segmentation Model with U-Net and TensorFlow Keras
Eran Feit via YouTube Medical Melanoma Detection - TensorFlow U-Net Tutorial
Eran Feit via YouTube Corona-Net
EuroPython Conference via YouTube