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This slide shows an introduction to Deep Learning in Julia with Flux including how to load data, train, save model and predict.
It also contains advanced topics e.g. how to use pretrained model, define own dataset iterator, ResNet-like layer and so on.
Due to the critical issue that BatchNorm layer, Advanced layer e,g. MobileNetV2 defined on this slide does not work on GPU, we can't use them right now, but in the future I believe this documentation will helpful for someone who want to learn or use Flux.
This slide is used for JuliaTokyo#8 conference on October 20, 2018