Combined with GPUs, Jupyter makes for fast development and fast execution, but it is not always easy to switch from a CPU execution context to GPUs and back. The speakers share best practices for doing deep learning with Jupyter and explain how to work with CPUs and GPUs more easily by using Elastic GPUs and quick-switching between custom kernels.

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