Description
Deep Learning for Image Segmentation with Python & Pytorch, Deep Learning for Image Segmentation with Python and Pytorch, is published by Udemy Academy. This course is designed to provide a comprehensive and practical experience in using deep learning techniques for semantic image segmentation problems. Are you ready to take your understanding of deep learning to the next level and apply it to real problems? In this course, you will learn how to use the power of deep learning to segment images and extract meaning from visual data. We’ll start by getting to know the basics of semantic segmentation using deep learning, then move on to implementing and training our models for semantic segmentation with Python and PyTorch.
This course provides a full experience of semantic segmentation using deep learning with Python and Python. At the end of this course, you will have the necessary knowledge and skills to start working on deep learning in semantic segmentation problems in your work or research. what an engineer vision Be it a computer, data scientist or developer, this course is the best way to take your understanding of deep learning to the next level. Let’s start this exciting deep learning journey for semantic segmentation with Python and PyTorch.
What you will learn
- Complete training on image semantic segmentation and its real applications with Python and PyTorch using Google Colab
- Deep learning architectures for semantic segmentation (UNet, DeepLabV3, PSPNet, PAN, UNet++, MTCNet, etc.)
- Data sets and data interpretation tools for semantic segmentation
- Implementation of data loading and data augmentation in PyTorch
- Learn performance metrics for evaluating segmentation models
- Transfer learning and pre-trained Deep Resnet architecture
- Test the segmentation training model and calculate IOU, IOU, Class-wise IOU, Pixel Accuracy, Precision, Recall and F-score
- Visualize the segmentation results and create a segmentation map of the predicted RGB output
Who is this course suitable for?
- This course is designed for people interested in learning how to apply deep learning techniques to solve real-world semantic segmentation problems using the Python programming language and the PyTorch deep learning framework.
- This course is designed for a wide range of students and professionals, including: machine learning engineers, deep learning engineers, data scientists, computer vision engineers, and researchers who want to learn how to use PyTorch to build and train deep learning models for Use semantic segmentation.
- Overall, this course is for anyone who wants to learn how to use deep learning to extract meaning from visual data and gain a deeper understanding of the theory and practical applications of semantic segmentation using Python and PyTorch.
Course specifications Deep Learning for Image Segmentation with Python & Pytorch
At the beginning of the course chapters on 1/2023
Deep Learning for Image Segmentation with Python & Pytorch course prerequisites
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Deep Learning for Semantic Segmentation with Python and Pytorch is taught in this course by following a complete pipeline from Zero to Hero
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No prior knowledge of Semantic Segmentation is assumed. Everything will be covered with hands-on training
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A Google Gmail account is required to get started with Google Colab to write Python Code
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