Warning: Please be aware that these videos are a snapshot, and as such may use an outdated version of the tutorial and/or Galaxy. Below the video you will find links to the tutorials as they appeared at the time of recording.
Warning: Please be aware that these videos are a snapshot, and as such may use an outdated version of the tutorial and/or Galaxy. Below the video you will find links to the tutorials as they appeared at the time of recording.
Below are video tutorials for this GTN session, created for various (past) events.
This 3-part session will introduce you to the world of deep learning and cover Feedforward Neural Networks (FNN), Recurrent Neural Networks (FNN), and Convolutional Neural Networks (CNN).
Deep Learning (Part 1) - Feedforward neural networks (FNN) (Tutorial)
| Description: | This hands-on tutorial covers Feedforward Neural Networks (FNN) |
| Length: | 1 hour 10 minutes |
| Captions: | Kaivan Kamali |
| Created: | 15 February 2021 |
| Materials: |
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| Support: | |
| Supported Servers: | Known Working Possibly Working |
Slides:
Tutorial:
Speaker
Deep Learning (Part 2) - Recurrent neural networks (RNN) (Tutorial)
| Description: | This hands-on tutorial covers Recurrenct Neural Networks (RNN) |
| Length: | 50 minutes |
| Captions: | Kaivan Kamali |
| Created: | 15 February 2021 |
| Materials: |
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| Support: | |
| Supported Servers: | Known Working Possibly Working |
Speaker
Deep Learning (Part 3) - Convolutional neural networks (CNN) (Tutorial)
| Description: | This hands-on tutorial covers Convolutional Neural Networks (CNN) |
| Length: | 1 hour |
| Captions: | Filippos Zacharopoulos |
| Created: | 15 February 2021 |
| Materials: |
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| Support: | |
| Supported Servers: | Known Working |