deep-learning-intro
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Episode 8 (optional): using a GPU
Rationale
Quickly show that using a GPU for training a network is both easy and speeds up training significantly.
Learning objectives
- Use a GPU when training a neural network.
- Describe why using a GPU speeds up training significantly.
Questions
- Why would I use a GPU when training a network?
- How do set Keras to use the GPU on my machine?
Keypoints
- When applying state-of-the-art deep learning techniques you need to use a GPU for training.
Outline
- Train a state-of-the-art network on a dataset on CPU, and let learners experience that this is too slow.
- Show how to enable GPU in keras
- Train the same network on the same dataset with GPU.
- Explain (superficially) why using a GPU speeds up learning so much
- Provide context and links to resources for setting this up on different systems (i.e. AWS, google cloud, DAS, SURF cloud)
We could use google colab, it provides free access to a notebook on a GPU machine.