[idunning]

As someone who almost exclusively uses Julia for their day-to-day work (and side projects), I think most of the author's thoughts about Julia are correct. I think the language is great, and using it makes my life better. There are some packages that are actually better than any of their equivalents in other languages, in my opinion.

On the other hand, I've also got a higher tolerance for things not being perfect, I can figure things out for myself (and luckily have the time do so), and I'm willing to code it up if it doesn't already exist (to a point). Naturally, that is not true for most people, and thats fine.

The author isn't willing to take the risk that Julia won't "survive", which is fair. Its definitely not complete yet, but its getting there. I am confident that it will survive (and thrive) though, and continue growing the not-insubstantial community. I have a feeling the author will find their way to Julia-land eventually, in a couple of years or so.

[ninjin]

As a fellow Julian, I agree. To reiterate what I said during my JuliaCon talk, I never truly understood what Rubyists meant when they said "optimised for happiness", Ruby never had that effect on me and I remained a happy Pythonista. However, Julia makes me feel this way and got me "hacking" again after having been in a bit of a slump.

That being said, we need to realise how young Julia actually is. Last Sunday marked six years since the first commit and the language has only been publicly available for three years. Julia is as old as Python was in 1994, or as old as Ruby was in 1998. Things are rough around the edges, but getting better. Things are missing in order for you to get productive quickly, but it is improving rapidly.

I do tell people around me that Julia is most likely the language that I love the most, I tell them about the features, my involvement, etc. But, when they say "That sounds awesome! Should I use it?", I hesitate and say, well, it depends. Are you already very productive in what you are currently using? Is speed an issue for you? If not, don't feel rushed, if you want to be a "pioneer" you certainly can be and we will welcome you. But consider your own situation before jumping ship, what do you need to be productive in your day-to-day job? However, keep an eye on Julia, because I am convinced that the cost of adaptation for you will continue to go down and if there is any language that has the chance to become "just right" for Machine Learning over the next couple of years, it is most likely going to be Julia.

[rasbt]

Thanks for the comment (I am the author of this article).

> I have a feeling the author will find their way to Julia-land eventually, in a couple of years or so.

I have a strong feeling that this will eventually happen :). In an ideal, less busy, world, I would love to use Julia alongside to explore and battle-test it further. Or even develop useful packages, libraries, and functions for it. The truth is, I am currently lacking the time to do that :(. I mean, Python works for me, and I am currently more into the scientific problem solving so that I don't have the time :(. When I say that Python works for me I mean that I am currently happy since it can do everything for me I need, however, this doesn't mean that Julia couldn't do certain things better ;).

Anyways, I really like your comment. I am wondering if you would be okay with it if I include it in a "Other people's experiences and opinions" section at the bottom. I think this would be extremely helpful for people who are new to the "data science field" -- my article is strongly biased towards Python as you noticed :P

[dnautics]

I think that the popularity of julia is exploding (but I'm biased - am writing an... interesting library for julia right now).

"There is really nothing wrong with R"

I think there is one thing wrong with R - it's name. Pretty much impossible to quickly google for help on it.

[idunning]

Sure, go ahead!

[Buttons840]

I've used Python professionally for 8 years, and it's my favorite language. I have used numpy and a scikit-learn a little bit. That said, I've really enjoying learning Julia recently. It's been easy to learn and it really does perform well (read: it's fast). In fact, I think learning Julia has been about as much work as learning something like numba would be, and gives similar (some say slightly better?) performance.

[noobermin]

I quickly glanced at your bio, but day-to-day work is that? Count yourself exceedingly lucky!

[pekk]

Could you name some of the packages you think are better than any of their equivalents?