I fully switched from Matlab to Julia to do my machine learning research two years ago. I really like Julia and never look back since then. With Julia, my workflow is more productive than before.
But now, I will start a deep learning project. I need to write a code similar to Bidirectional LSTM - CRF, but with my own CRF-like implementation. I also need to customize the details of some layers implementation.
I found an example on how to write Bi-LSTM-CRF code in pytorch http://pytorch.org/tutorials/beginner/nlp/advanced_tutorial.html
which seems to be a good start for me.
I am also aware about deep learning packages in Julia: Flux.jl and Knet.jl. But I am not sure if those package fit well with my project. I cannot find any implementation of Bi-LSTM-CRF in those package.
Should I jump to Python and use PyTorch or keep using Julia? Any suggestion?