MLJ doesn't concern me in a bad way. At it's heart it's an abstraction for ML components across many packages with some machinery on top for parameter tuning, etc. That's fine.
What it's missing is ... impactful improvements on the failures of libraries like this. Docs need more examples and less pointers to packages that wrap other packages(albeit they are written well). Despite being a multi-year long effort by very big names it still feels incomplete, and if someone wasn't sold on Julia there is technically no reason not to use R or Python or Matlab. Missed opportunity is all
Julia is great for NEW ML research. But it has serious downsides for mundane or even above average production work...
Flux has historically been more of a research project then a production library. That's ok, it holds a lot of promise. But, time to first gradient can be excessive. Minutes to discover a small bug excessive. Last I checked all of the adjacent libraries around it were broken due to incredibly frequent changes to the API.
Mlj doesn't impress me. There was a serious opportunity to change the way people do routine modelling using the strengths of julia. They basically made a half baked sklearn instead. Missed opportunity in my mind.
In general the components for statistical libraries are exceptional. However the ecosystem falls short to do things with them in a stable way.
The best libraries imo for data science work stem from the excellent db adapters, optimization library's, data frames jl, Turing jl, etc. Anything beyond that and it's usually better off just rolling your own or using another language all together... Current state of production, ie not code running a notebook is also ok at best...
What it's missing is ... impactful improvements on the failures of libraries like this. Docs need more examples and less pointers to packages that wrap other packages(albeit they are written well). Despite being a multi-year long effort by very big names it still feels incomplete, and if someone wasn't sold on Julia there is technically no reason not to use R or Python or Matlab. Missed opportunity is all