U-Net Courses and Certifications

Eran Feit

Before You Train a U-Net - Car Segmentation Tutorial

Master U-Net image segmentation from scratch with PyTorch, building a complete car segmentation model from dataset preparation to inference on the Carvana challenge.

• YouTube
• 39 minutes
• On-Demand
• Free Video

Eran Feit

How I Trained U-Net to Detect Dolphins - Segmentation Tutorial

Master U-Net image segmentation by building a complete dolphin detection model from raw data to real-time inference using Python, TensorFlow, and OpenCV.

• YouTube
• 1 hour
• On-Demand
• Free Video

Aladdin Persson

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

Learn to implement U-NET for image segmentation from scratch, covering model architecture, dataset preparation, training process, and evaluation techniques in PyTorch.

• YouTube
• 52 minutes
• On-Demand
• Free Video

Eran Feit

Creating an Animal Segmentation Model with U-Net and TensorFlow Keras

Learn to implement and train a U-Net model for animal segmentation using TensorFlow/Keras. Covers data preprocessing, model architecture, training, and evaluation with practical code examples.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Eran Feit

Medical Melanoma Detection - TensorFlow U-Net Tutorial

Step-by-step guide to implementing a U-Net model for melanoma detection using TensorFlow/Keras, covering data preparation, augmentation, model building, training, testing, and result visualization.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Dyalog User Meetings

Implementing the Convolutional Neural Network U-Net in APL

Implement U-Net CNN in APL, exploring its architecture, key functions, and APL's unique features for efficient machine learning experimentation and problem-solving in AI.

• YouTube
• 23 minutes
• On-Demand
• Free Video

ACM SIGPLAN

U-Net CNN in APL: Exploring Zero-Framework, Zero-Library Machine Learning

Explore U-Net CNN implementation in APL, comparing performance and clarity with PyTorch. Discover APL's potential for concise, transparent machine learning code using modern GPU-supported compiler.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Eran Feit

Dust-Storm Image Segmentation with VGG16 U-Net - Binary Segmentation

Master dust-storm image segmentation with VGG16 U-Net in TensorFlow 2, from building the model to training and inference on satellite imagery that separates storm plumes from background terrain.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Eran Feit

How to Actually Remove Any Background with U²-Net

Master background removal techniques with U²-Net in TensorFlow, from dataset preparation to model training and inference. Learn to build a complete pipeline for clean, precise image segmentation without green screens or blurry edges.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Conference GSI

Chan Vese Attention U-Net - An Attention Mechanism for Robust Segmentation

Explore an innovative attention mechanism for robust image segmentation using Chan Vese Attention U-Net, enhancing segmentation accuracy and efficiency.

• YouTube
• 20 minutes
• On-Demand
• Free Video

The Neural Net Framework: A Gentle Introduction: Wolfram U Class

Explore neural networks as differentiable programs, build models for regression and classification, and learn to train, fine-tune, and validate their performance using Wolfram Language.

• Wolfram U
• 1 hour
• On-Demand
• Free Online Course

Deploying and Running a Custom Neural Net on Your Phone - Wolfram U Class

Create and deploy a custom neural net image classifier for iPhone, from importing data to training the model and deploying the app, using Wolfram technology and external tools.

• Wolfram U
• 28 minutes
• On-Demand
• Free Online Course

Deep Learning for Computer Vision

22 ratings at Coursera

Master CNNs, autoencoders, GANs, ResNet, and U-Net architectures to build powerful computer vision models for image classification, generation, and segmentation tasks.

• Coursera
• 14 hours 5 minutes
• On-Demand
• Paid Course

Coursera

Fine-tuning Image Models with Diffusion

Master diffusion model fine-tuning with LoRA, DreamBooth, and ComfyUI to create custom image generation models for production-quality results.

• Coursera
• 8 hours 5 minutes
• On-Demand
• Paid Course

DigitalSreeni

Semantic Segmentation of Aerial Imagery Using U-Net

Learn to preprocess aerial imagery, train U-net for semantic segmentation, and make predictions using Python, focusing on data preparation and model implementation for satellite image analysis.

• YouTube
• 42 minutes
• On-Demand
• Free Video