Deep Learning with PyTorch : Image Segmentation

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Course Overview

In this 2-hour project-based course, you will be able to : - Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair. - Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library. - Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.

Course FAQs

What are the prerequisites for 'Deep Learning with PyTorch : Image Segmentation'?

Prerequisites for this continuing education class are set by Coursera Project Network. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.

Will I receive a certificate for this CE class?

Yes, upon successful completion, Coursera Project Network typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.

How long does this online course take to complete?

Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.