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Emotion AI
Facial Key-points Detection
In this 1-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Deep Learning, Convolutional Neural Networks (CNNs) and Residual Neural Networks.
- Import Key libraries, dataset and visualize images.
- Perform data augmentation to increase the size of the dataset and improve model generalization capability.
- Build a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend.
- Compile and fit Deep Learning model to training data.
- Assess the performance of trained CNN and ensure its generalization using various KPIs.
- Improve network performance using regularization techniques such as dropout.
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Rating | Not enough ratings |
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Length | 2 weeks |
Effort | 3 hours |
Starts | Jul 3 (45 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Ryan Ahmed |
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 | 3 hours |
Starts | Jul 3 (45 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Ryan Ahmed |
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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