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dawndrain commented on Lessons Learned from Two Years as a Data Scientist   dawndrain.github.io/brain... · Posted by u/jessedrain
listenallyall · 5 years ago
This reads like a pretty "wet-behind-the-ears" professional who doesn't know what he doesn't know.

> There's no Java awfulness like ... instead it's just `cars = []`

I mean, there's very good reasons for static typing. And if he was using Kotlin, he could specify whether the variable `cars` was itself immutable and whether the list was immutable (`val/var cars : List<String>/MutableList<String>`

> notebooks

yea, Jupyter kernels exist for almost every language. This is not a Python advantage.

> debugging

Good IDEs have the ability to set breakpoints, inspect variables, test methods, etc.

> type hints

"oh, forget what I said earlier about how Java had ugly boilerplate, now I have an `import` and a type def after all" - except nothing here is actually enforced

> parallelism

parallelism is relative... a lot of compiled JVM code will run much faster than Python to start with, and even with `multiprocessing`, Python won't catch up (and JVM languages have their own concurrency solutions, of course)

> I've put a large chunk of my money in leveraged index funds and etfs.

Written by a person who's never seen the slightest hint of a bear market, or rising interest rates. That's ok, you wouldn't be the first smart person to be seduced by leverage: https://www.investopedia.com/terms/m/myron-scholes.asp

> Stimulants like caffeine, adderall, and modafinil are magic... People do stay on adderall and modafinil indefinitely

Look, I'm no doctor (and I'm aware I'm out of the loop on things like this), but mental & concentration stimulants are the kinds of things associated with old people, not recent graduates.

dawndrain · 5 years ago
Certainly lots of things to learn still.

Going point by point:

It's not "he" it's "she".

I don't think it's controversial that you can be much more concise with python. My experience first learning Java was that everything was 2-3x as verbose as in python. The difference is smaller if you're using type hints in python, but it's still more concise.

I talked about repl's/notebooks for other languages. They're still an especially great tool for python/data science since they make it very easy to visualize data and share analyses.

I played around with breakpoints in pycharm and I don't think it would work for me. You need to run your code from pycharm in debug mode for the breakpoint to trigger, whereas I always run things from the command line or a notebook.

I believe you that there are times when python is slower. At least it's not noticeably slower when simply calling C behind the scenes or when you're i/o blocked anyway.

Re investing, I mean, everyone has seen phenomenal returns since they were born: this century is unprecedented. Also there was the pandemic crash very recently, so everyone has experienced an extremely harsh (albeit brief) bear market too. LTCM was like 100x-leveraged, which I would not advocate for, since you'll almost certainly get wiped out if you hold that position for more than a few hours...

Eh, lots of kids have add, and like 10% of college students used adderall in 2016 according to the first hit on google. In any case they've been magic for me the few times I've tried them e.g. working 12+ good hours in a day.

dawndrain commented on Lessons Learned from Two Years as a Data Scientist   dawndrain.github.io/brain... · Posted by u/jessedrain
ZephyrBlu · 5 years ago
I was hoping for more DS related stuff. It almost sounds like you're learning to be a SWE!

The investing section is curious.

> On brilliant advice from the man who arguably went from mere millions to decabillions faster than anyone in modern history, I've put a large chunk of my money in leveraged index funds and etfs

Who are you referencing here and did you do any DD other than taking his advice?

I'm wondering what the downsides of leveraged index funds and ETFs are since I'm not sure how they work.

dawndrain · 5 years ago
> I was hoping for more DS related stuff. It almost sounds like you're learning to be a SWE!

It kind of felt that way too :). Some more data sciency things were learning how transformers work, hacking pytorch, using visualization tools like tensorboard and wandb, web scraping, better using parallelism, tuning hyperparameters (mostly the learning rate tbh), better fluency with the command line than I assume most swe's need, getting very comfortable inspecting data, making experiments more reproducible, reading lots of papers, writing papers, and trying (somewhat half-heartedly) to get published.

dawndrain commented on Lessons Learned from Two Years as a Data Scientist   dawndrain.github.io/brain... · Posted by u/jessedrain
ZephyrBlu · 5 years ago
I was hoping for more DS related stuff. It almost sounds like you're learning to be a SWE!

The investing section is curious.

> On brilliant advice from the man who arguably went from mere millions to decabillions faster than anyone in modern history, I've put a large chunk of my money in leveraged index funds and etfs

Who are you referencing here and did you do any DD other than taking his advice?

I'm wondering what the downsides of leveraged index funds and ETFs are since I'm not sure how they work.

dawndrain · 5 years ago
> did you do any DD other than taking his advice?

I did some backtesting simulations that made leveraged investing look pretty awesome. The effective borrow rate for funds like spxl is crazy low, way better than if I were to borrow myself. (Also, fwiw I was pretty conservative and am overall only around 2x-leveraged.)

The internet is very opposed to leveraged investing imo, but I think most of the concerns are pretty dumb. There was this one blog post where this guy ran ten simulations of his own, most of which showed the leveraged portfolio doing comparably to the baseline, but one a couple showed it doing worse and one saw the leveraged portfolio 100x'ing or something... and he concluded that it wasn't worth it??

People will also appeal to volatility drag as a superficially sophisticated knockdown (in short, imagine all four two-step paths in which the market goes up or down by 10% at each step. Then the baseline market averages out to (.81 + .99 + .99 + 1.21)/4 = 1, and a 3x leveraged portfolio averages out to (.49 + .91 + .91 + 1.69)/4 = 1. Volatility drag is those two middle worlds where the leveraged portfolio does badly despite the market as a whole basically ending up where it started.

dawndrain commented on Lessons Learned from Two Years as a Data Scientist   dawndrain.github.io/brain... · Posted by u/jessedrain
qsort · 5 years ago
> Google doesn't allow any production-level projects to be written in python due to safety concerns

Is this actually true? If it's true that Google doesn't allow Python in production, it seems unlikely that it's due to security concerns.

dawndrain · 5 years ago
I heard this second-hand, not totally sure it's true

u/dawndrain

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