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Fundamentals of CNNs and RNNs
This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas.
In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs.
The goal of this course is to give learners basic understanding of CNNs and RNNs. Throughout this course, you will be equipped with skills required for computer vision and natural language processing.
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| Rating | Not enough ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4 hours/week |
| Starts | Jun 26 (47 weeks ago) |
| Cost | $49 |
| From | Sungkyunkwan University via Coursera |
| Instructor | Jee-Hyong Lee |
| Download Videos | On all desktop and mobile devices |
| Language | Korean |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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| Rating | Not enough ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4 hours/week |
| Starts | Jun 26 (47 weeks ago) |
| Cost | $49 |
| From | Sungkyunkwan University via Coursera |
| Instructor | Jee-Hyong Lee |
| Download Videos | On all desktop and mobile devices |
| Language | Korean |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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