Deep Learning with PyTorch : Image Segmentation

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Offered byCoursera

Deep Learning with PyTorch : Image Segmentation
at
Coursera
Overview

Gain a comprehensive overview of the Deep Learning principles and concepts

Duration	2 hours
Mode of learning	Online
Schedule type	Self paced
Difficulty level	Intermediate
Credential	Certificate

Deep Learning with PyTorch : Image Segmentation
at
Coursera
Course details

What are the course deliverables?

Use U-Net architecture for segmentation
Create train function and evaluator for training loop

More about this course

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

Deep Learning with PyTorch : Image Segmentation
at
Coursera
Curriculum

Set up colab runtime environment

Setup Configurations

Augmentations

Custom Dataset

Load Dataset into batches

Create Segmentation Model

Create Train and Eval Function

Train Model

Inference

Deep Learning with PyTorch : Image Segmentation
at
Coursera
Faculty details

Parth Dhameliya

Parth is a Machine Learning Instructor at coursera. His area of interests includes AI in healthcare,Deep Learning, Machine Learning and Data Science.He focus more on building better medical diagnostic models and on creating computer vision based projects.