State of Machine Learning in Julia

Re:State of Machine Learning in Julia by usgroup on Wednesday January 12, 2022 @06:52AM (#29905116)

The responses confuse "machine learning" with neural networks so far as I can see. I do lots of statsy things: good luck with that outside of R.

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Re:State of Machine Learning in Julia by fault1 on Wednesday January 12, 2022 @08:13AM (#29905913)

turing, mlj, etc are quite good.

https://turing.ml/stable/

https://alan-turing-institute.github.io/MLJ.jl/dev/about_mlj...

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Re:State of Machine Learning in Julia by usgroup on Wednesday January 12, 2022 @11:28AM (#29908828)

Until you've used: https://r-nimble.org/

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Re:State of Machine Learning in Julia by fault1 on Wednesday January 12, 2022 @02:25PM (#29911618)

looks good!

The ecosystem in Julia is quite strong for MCMC libs because people do not have to lower something to C++ to develop such a library: https://discourse.julialang.org/t/mcmc-landscape/25654/

Of course, for users, they might prefer something like Turing, but I think the Julia tends to blur the differences between user and developer more so than in most other languages (for good or worse) since everything is in one language.

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Re:State of Machine Learning in Julia by malshe on Wednesday January 12, 2022 @12:38PM (#29910108)

Thanks! Didn't know this exists

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Re:State of Machine Learning in Julia by dunefox on Wednesday January 12, 2022 @02:22PM (#29911584)

> good luck with that outside of R.

There's always RCall for R inside of Julia, the best of both worlds.

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Re:State of Machine Learning in Julia by jiggunjer on Wednesday January 12, 2022 @06:58AM (#29905157)

Even professors doing trendy "AI" research conflate the two terms.

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Re:State of Machine Learning in Julia by dagw on Wednesday January 12, 2022 @10:35AM (#29907778)

Even professors doing trendy "AI" research conflate the two terms.

Only because doing "AI" gets you bigger grants.

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Re:State of Machine Learning in Julia by kgwgk on Wednesday January 12, 2022 @11:33AM (#29908944)

Tibshirani's Glossary

   Machine learning               Statistics

   network, graphs                model
   weights                        parameters
   learning                       fitting
   generalization                 test set performance 
   supervised learning            regression/classiﬁcation
   unsupervised learning          density estimation, clustering

   large grant = $1,000,000       large grant = $50,000

   nice place to have a meeting:  nice place to have a meeting:
    Snowbird, Utah, French Alps    Las Vegas in August

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Re:State of Machine Learning in Julia by sethaxen on Wednesday January 12, 2022 @09:21AM (#29906603)

Statistics is usually considered a subset of ML, except maybe by statisticians.

While R definitely leads the pack on variety of useful stats packages, there are excellent tools for certain tasks in other languages. I do a lot of probabilistic programming, and PyMC in Python and Turing in Julia are excellent packages. And both languages have official Stan interfaces. Not knowing R has not been a problem for me.

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Re:State of Machine Learning in Julia by dmicah on Wednesday January 12, 2022 @10:32AM (#29907730)

I'm sure it depends on your vantage point, but I would argue that ML is more likely to be considered a subset of Statistics than the other way around.

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Re:State of Machine Learning in Julia by kgwgk on Wednesday January 12, 2022 @11:26AM (#29908791)

Let the machine decide:

https://www.google.com/search?q=%22statistics+is+a+subset+of...

1 result

https://www.google.com/search?q=%22machine+learning+is+a+sub...

2 results

Machine learning is a subset of statistics.

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Re:State of Machine Learning in Julia by usgroup on Wednesday January 12, 2022 @11:26AM (#29908794)

It just means that you have problems you're not aware of :-)

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Re:State of Machine Learning in Julia by sethaxen on Thursday January 13, 2022 @03:58AM (#29918388)

or that the tooling for the problems I do have is adequate in multiple languages.

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