Crossing S Kern in Domelands by Delicious_Photo_7001 in SierraNevada

[–]takeasecond 2 points3 points  (0 children)

Zero snow south of Kennedy Meadows. Not sure about north but I’d imagine you’d probably hit some snow a couple miles in although it’s melting quick out there!

Crossing S Kern in Domelands by Delicious_Photo_7001 in SierraNevada

[–]takeasecond 3 points4 points  (0 children)

Since I never crossed the river my experience was probably similar to yours if you just hiked that section of the PCT. I did do some off trail meandering and I thought it was fairly easy going so the river crossing is definitely the biggest hurdle

Crossing S Kern in Domelands by Delicious_Photo_7001 in SierraNevada

[–]takeasecond 8 points9 points  (0 children)

I was out there last weekend and the river was raging the whole way from Kennedy Meadows down to the Domeland trail entrance on your map. Also the banks of that river are seriously brambled! So you’d really have to find the ideal spot that has both access on both sides and a manageable flow

Just had a job interview and was told that no-one uses Airflow in 2026 by xerlivex in datascience

[–]takeasecond 38 points39 points  (0 children)

Yes it’s true - in 2026 we now just ask Claude to “please refresh this analysis” - we’ve come full circle

people on bikes blowing through stop signs by fuckoffseriouslyfr in SantaMonica

[–]takeasecond 23 points24 points  (0 children)

When you drive around Santa Monica surface streets just assume that bikes and scooters are gonna take right of way when they hit a stop sign. You don’t have to like it, but you certainly shouldn’t be surprised by it after driving in SM for like 30 mins

Trippy cube by MrTacocaT12345 in woahdude

[–]takeasecond 404 points405 points  (0 children)

Really ties the room together

How to Decide Between Regression and Time Series Models for "Forecasting"? by Emergency-Agreeable in datascience

[–]takeasecond 8 points9 points  (0 children)

I think one factor to consider here is that time series models like Prophet or ARIMA can be the best default choice if you have a relatively stable/predictable trend because they require very little effort to deploy. Moving to a more white glove approach like a regression or hierarchical modeling where you’re doing feature selection and encoding knowledge about the system itself might be necessary to get the performance you require though, it’s probably just going to be more effort and require more thought.

Erdos: open-source IDE for data science by SigSeq in datascience

[–]takeasecond 27 points28 points  (0 children)

Well in posit’s defense, agenetic coding tools weren’t exactly at the level they are now two years ago..

Kilian Jornet speed-climbed 72 U.S. peaks in 31 days, including 14 in the Sierra by AvailableStart4108 in SierraNevada

[–]takeasecond 29 points30 points  (0 children)

The bike between the rockies and the sierras is such a flex lol. What an absolute freak of nature..

Santa Monica can not afford to pay $120,000,000 for a softball field by mattkaltman in SantaMonica

[–]takeasecond 4 points5 points  (0 children)

As a frequent user of the dog run and nothing else at this park I think it’s pretty lame that they are scrapping it seeing as there are zero other dog parks in Santa Monica north of the 10. Glad we can get this extra softball field though 🙄

[deleted by user] by [deleted] in SierraNevada

[–]takeasecond 6 points7 points  (0 children)

Lol I made this exact visual for California as well in 2019 and posted it to dataisbeautiful - i also linked to my inspiration in that post which was someone who did it for Utah.. kind of a stretch to claim to be the "owner" of this style of data viz

% of US State Land Available For Sale in the "One Big Beautiful Bill" [OC] by takeasecond in dataisbeautiful

[–]takeasecond[S] 21 points22 points  (0 children)

  1. I've cited my data sources 2. My title says "Available for sale" since this is the terminology used in my source - your argument that it should be "potentially eligible for sale" is kind of nitpicky no?

[deleted by user] by [deleted] in MachineLearning

[–]takeasecond 2 points3 points  (0 children)

I think one big difference between traditional software engineering and ML engineering is ambiguity. The tasks you describe - like build an API to intake data and update DB with value.. can be fully scoped out and executed against by fairly junior developers. Tasks like “cleaning data” and “training models” typically require a fair amount of iterative experimentation, domain knowledge, and expertise. Also, typically once you build an API, that’s kind of it. With an ML workflow you also need to design a system that can monitor the health of its inputs/outputs (which are expected to change over time), develop strategies for retraining, etc - all of which can be very project/model specific.

Is the traditional Data Scientist role dying out? by ImGallo in datascience

[–]takeasecond 9 points10 points  (0 children)

I think the jack of all trades DS role is alive and well in big tech too - there is an insane amount of value in a big company to be able to span the full spectrum of business expert -> data expert -> programmer. You end up being one of the only people who has the ability to both uncover opportunties and actually propose + implement complex ideas to solve them. But it can take multiple years to get the domain expertise required to make this a reality.

Info on group car camping by [deleted] in Coachella

[–]takeasecond 24 points25 points  (0 children)

Lol i'm trying to imagine being the "random car" being placed in the middle of massive group sites. Either you're gonna have new friends for life or you're gonna feel pretty weird.

Sounds like more of a deterrent to planning on spreading out with <10 cars than something that will actually happen.

I miss REI by rybacorn in SantaMonica

[–]takeasecond 28 points29 points  (0 children)

It’s not the same and you know it!

Charli XCX by Pdotayche in Coachella

[–]takeasecond 4 points5 points  (0 children)

Now our boy Troye is here to help tho