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Facial Expression Recognition with PyTorch
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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Rating | Not enough ratings |
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Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 17 (21 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Parth Dhameliya |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Software Development Machine Learning |
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Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 17 (21 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Parth Dhameliya |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Software Development Machine Learning |
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