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Mastering Image Segmentation with PyTorch using Real-World Projects
Mastering Image Segmentation with PyTorch using Real-World Projects

Mastering Image Segmentation with PyTorch using Real-World Projects: Master the art of image segmentation with PyTorch through hands-on training and real-world projects

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Profile Icon Bert Gollnick
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€8.99 €52.99
Video Sep 2023 5hrs 5mins 1st Edition
Video
€8.99 €52.99
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Renews at €18.99p/m
Arrow left icon
Profile Icon Bert Gollnick
Arrow right icon
€8.99 €52.99
Video Sep 2023 5hrs 5mins 1st Edition
Video
€8.99 €52.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€8.99 €52.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Understand key concepts from tensors to advanced segmentation models
  • Implement real-world image segmentation projects with confidence
  • Ideal for both beginners and experienced computer vision enthusiasts

Description

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. You will start by exploring tensor handling, automatic gradient calculation with autograd, and the fundamentals of PyTorch model training. As you progress, you will build a strong foundation, covering critical topics such as working with datasets, optimizing hyperparameters, and the art of saving and deploying your models. With a robust understanding of PyTorch, you will dive into the heart of the course—semantic segmentation. You will explore the architecture of popular models such as UNet and FPN, understand the intricacies of upsampling, grasp the nuances of various loss functions, and become fluent in essential evaluation metrics. Moreover, you will apply this knowledge in real-world scenarios, learning how to train a semantic segmentation model on a custom dataset. This practical experience ensures that you are not just learning theory but gaining the skills to tackle actual projects with confidence. By course end, you will wield the power to perform multi-class semantic segmentation on real-world datasets.

Who is this book for?

This course is tailored to a diverse audience, making it accessible to both newcomers and experienced individuals in the field of computer vision. If you are an aspiring developer eager to delve into image segmentation or a data scientist aiming to expand your deep learning repertoire, this course is for you. While no prior image segmentation knowledge is required, a fundamental understanding of Python is essential. Familiarity with machine learning concepts will be beneficial.

What you will learn

  • Implement multi-class semantic segmentation with PyTorch
  • Explore UNet and FPN architectures for image segmentation
  • Understand upsampling techniques and their importance in deep learning
  • Learn the theory behind loss functions and evaluation metrics
  • Perform efficient data preparation to reshape inputs to the appropriate format
  • Create a custom dataset class for image segmentation in PyTorch

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 29, 2023
Length: 5hrs 5mins
Edition : 1st
Language : English
ISBN-13 : 9781801817356
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Product Details

Publication date : Sep 29, 2023
Length: 5hrs 5mins
Edition : 1st
Language : English
ISBN-13 : 9781801817356
Category :
Languages :
Tools :

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Table of Contents

4 Chapters
Course Overview and Setup Chevron down icon Chevron up icon
PyTorch Introduction (Refresher) Chevron down icon Chevron up icon
Convolutional Neural Networks (Refresher) Chevron down icon Chevron up icon
Semantic Segmentation Chevron down icon Chevron up icon
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