The tutorial for this notebook can befound here

Key concepts include:

[ ] convolution
[ ] relu (rectified linear activations
[ ] pooling (max pooling)
[ ] normalization (local response normalization)
[ ] Visualization using tensorboard
[ ] Evaluating moving average of learned parameters and boost predictive performance
[ ] pre-fetching queues for input data to avoid disk latency.

Multi-GPU is not covered here.



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