Back to Facial Expression Recognition with PyTorch
Learner Reviews & Feedback for Facial Expression Recognition with PyTorch by Coursera Project Network
14 ratings
About the Course
In this 2-hour long guided-project course, you will load a pretrained state of the art model CNN and you will train in PyTorch to classify facial expressions. The data that you will use, consists of 48 x 48 pixel grayscale images of faces and there are seven targets (angry, disgust, fear, happy, sad, surprise, neutral). Furthermore, you will apply augmentation for classification task to augment images. Moreover, you are going to create train and evaluator function which will be helpful to write training loop. Lastly, you will use best trained model to classify expression given any input image.
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1 - 4 of 4 Reviews for Facial Expression Recognition with PyTorch
By Dvsn S
•Aug 14, 2022
It is a good approach to create a facial expression regonition and code explanation is very well, i am happy to learn
By Alex W
•Sep 5, 2022
This course is good for practing python scripts by creating a facial recognition AI. The course offers an exercise in python, nothing more.
By M. A K
•Aug 17, 2022
I dislike this course. Things weren't explained at all and the course finished without even testing the model.
By Gencho Z
•Aug 5, 2022
1-start because the video for last section is missing. Otherwise the project is OK.
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