Mastering Image Segmentation with PyTorch

Master the art of image segmentation with PyTorch with hands-on training and real-world projects

Published 1/2023
Created by Bert Gollnick
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 44 Lectures ( 5h 1m ) | Size: 2.2 GB

What you’ll learn
implement multi-class semantic segmentation with PyTorch on a real-world dataset
get familiar with different architectures like UNet, FPN
understand theoretical background, e.g. on upsampling, loss functions, evaluation metrics
perform data preparation to reshape inputs to appropriate format

Requirements
Basic Python knowledge

Description

Welcome to “Mastering Image Segmentation with PyTorch”! In this course, you will learn everything you need to know to get started with image segmentation using PyTorch.Image segmentation is a key technology in the field of computer vision, which enables computers to understand the content of an image at a pixel level. It has numerous applications, including autonomous vehicles, medical imaging, and augmented reality.This course is designed for both beginners and experts in the field of computer vision. If you are a beginner, we will start with the basics of PyTorch and how to use it for simple modeling. Then, you will learn how to implement popular semantic segmentation models such as FPN or U-Net.By the end of this course, you will have the skills and knowledge to tackle real-world semantic segmentation projects using PyTorch.So why wait? Join me today and take the first step towards mastering image segmentation with PyTorch!In my course I will teach you:Tensor handlingcreation and specific features of tensorsautomatic gradient calculation (autograd)Modeling introduction, incl. Linear Regression from scratchunderstanding PyTorch model trainingBatchesDatasets and DataloadersHyperparameter Tuningsaving and loading modelsConvolutional Neural NetworksCNN theorylayer dimension calculationimage transformationsSemantic SegmentationArchitectureUpsamplingLoss FunctionsEvaluation MetricsTrain a Semantic Segmentation Model on a custom DatasetEnroll right now to learn some of the coolest techniques and boost your career with your new skills.Best regards,Bert

Who this course is for
Developers who want to understand and implement Image Segmentation
Data Scientists who want to broaden their scope of Deep Learning techniques