What a profound criticism. If data scientists can't use Julia then they're not great data scientists - you have RCall and PyCall, Flux, Knet, MLJ, plotting libraries, etc. It has built-in and user-defined types, threads, multiple dispatch, ...
"Please don't think that Julia is only useful for 1. custom units 2. custom GPU kernels 3. Custom array types 4. custom bayesian priors. 5. AD through custom types 6. Task based parallelism 7. symbolic gradients with modeling toolkit 8. Agent based modeling 9. physics informed neural networks 10. abstract tables types ..."
What a profound criticism. If data scientists can't use Julia then they're not great data scientists - you have RCall and PyCall, Flux, Knet, MLJ, plotting libraries, etc. It has built-in and user-defined types, threads, multiple dispatch, ...
"Please don't think that Julia is only useful for 1. custom units 2. custom GPU kernels 3. Custom array types 4. custom bayesian priors. 5. AD through custom types 6. Task based parallelism 7. symbolic gradients with modeling toolkit 8. Agent based modeling 9. physics informed neural networks 10. abstract tables types ..."