I've started working with Flux [1] in Julia, and it's so elegant and such a great experience :). Just look at this definition of a U-net model for image segmentation: https://gist.github.com/haampie/bceb1d59fd9a44f092f913062e58.... Apart from that, you can write your own custom loss functions in pure Julia that run efficiently on the GPU, language level automatic differentiation, proper integration with other packages. If people are moving away from Tensorflow, then Flux could be a solid alternative as well.
[1] https://github.com/FluxML/Flux.jl