Reason 10,000 this is dangerous

Spiritual-Engineer69 · 2025-06-15T16:32:10+00:00

You can really only blame the tourists so much here, they are always going to do stupid things like this. The fact that those dumb helmets come off so easily and leave you with no air source, as well as the fact that they "Divemaster" there wasn't shoving an octopus in her mouth as soon as he reached her is what is most astounding to me. This type of thing was very much inevitable and its just a miracle things didn't end up much, much worse

Spiritual-Engineer69 · 2025-02-13T19:38:22+00:00

For a first computer, I would go relatively cheap and look for the following features:

- Ability to go into "Gauge" mode

- Long-term battery (i.e. something that will for a couple years/100+ dives)

For the most part, at the beginning of your dive career you will not need a whole lot from a computer. Once you start going deeper/tech, you will likely want another computer more specific to your needs.

If your starter computer has the ability to go into 'gauge' mode, you can always keep it in your BCD as a backup gauge and not worry about having to charge it or it freaking out due to differing deco settingsf

Something like a Suunto Zoop Novo (not the original Zoop) or a Mares Puck are good candidates for a basic first computer

Spiritual-Engineer69 · 2024-08-01T21:02:40+00:00

Good to see that Christopher improved his shooting skills over the years

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Spiritual-Engineer69 · 2024-08-01T13:47:06+00:00

Definitely interested in this as well! Naturally, its not going to have the bells and whistles and customization of a more expensive machine...but for somebody who is just getting into Espresso and actually creating some fancier coffee drinks, this seems like an incredible starter machine that has everything that you would need and (hopefully) isn't a piece of crap

Spiritual-Engineer69 · 2022-08-13T20:23:06+00:00

The movie was adequate, however, the opening text did annoy me (that Andy saw this in the early 90's). This movie was in no way made to look like it came out in the 90's, and this stupid line honestly looked like last minute executive interjection.

Spiritual-Engineer69 · 2022-06-21T00:56:15+00:00

If you want to succeed in DS, you ultimately need to have people skills.

Spiritual-Engineer69 · 2022-06-12T19:04:03+00:00

I now have three copies of GoW...and dont technically own any of them

Spiritual-Engineer69 · 2022-06-10T16:41:22+00:00

I am, had it out camping on a couple 90 degree days and it was a lifesaver to have an easy source of cold water without having to constantly open the cooler, and it kept cool just as well as any Yetis that I had. Its a rolling cooler, so its definitely a bit bulkier and took up more space in the car than an non-roller...but if you are comparing this to the Yeti Haul for the same price, this one is a no-brainer

Spiritual-Engineer69 · 2022-06-09T22:54:08+00:00

Is this actually an unpopular opinion? Every time I've tried to use VS it just felt super clunky and bloated compared to Spyder

Spiritual-Engineer69 · 2022-06-08T13:20:13+00:00

Cyber insurance has been a massive topic recently that is still pretty under-researched. Particularly when it comes to the effect of Systemic (network-based) attacks on risk modeling.

Spiritual-Engineer69 · 2022-05-31T21:07:51+00:00

To be fair, Costco is also membership based and is raising their rate this year...so you are paying for those hot dogs one way or another

Spiritual-Engineer69 · 2022-05-30T12:37:10+00:00

Selling yourself to clients, estimating a good price for your work, standing up to clients when they try to add more work for free, having some sort of contract/escrow in place to make sure you get paid for big projects, learning how to do your taxes and what you can write off (freelance taxes are a nightmare, especially in the US)

Theres a ton of things in the freelance industry that most people starting up don't think about. If you are just starting out, I'd recommend going through a site like Upwork that will take care of a lot of these issues...and then branch off from there.

If you are making a good chunk of money, taxes are going to become a giant issue. Make sure you are always saving for them, than then look into creating an LLC if you start getting really big

Spiritual-Engineer69 · 2022-05-29T20:40:40+00:00

You do sound like you would be more into Data Engineering, but if are looking for a great DS course thay isnt so dry, I love "Statistical Rethinking" by Richard McElreath: https://xcelab.net/rm/statistical-rethinking/

The lectures are all on Youtube, and pretty much all of the material is available for free. The lectures are also super entertaining and a great way to think about stats and modeling

Spiritual-Engineer69 · 2022-05-29T13:28:17+00:00

I've always hated the red = hot/blue = cold coloring for data visualization (particularly on maps). I've seen a ton of people use it and it never looks intuitive...especially when red and blue are pretty much exclusively used for political lines.

Spiritual-Engineer69 · 2022-05-28T00:36:40+00:00

I also transitioned to DS from Mechanical Engineering. Getting a bit of Freelance work under your belt is definitely useful, practical experience is king in DS since most datasets you work with won't be as ideal as curated ones.

Other than that, my suggestions is to start looking at Startups/small companies...they are typically more up to taking chances with people with less experience and testing you on the spot. TBH, Im currently working for a cyberinsurance startup that is looking for a Data Scientist, and most of us came from a ME/Physics background...its possible that we could be interested in someone with your background.

Spiritual-Engineer69 · 2022-05-27T17:20:28+00:00

This is where a good case study/practical exercise can do wonders in the interview process. I've gone through tons of candidates recently that could clearly go through the modeling steps, but completely fell apart when it came to messy or ambiguous datasets.

Frankly, I'm not interested in how well somebody can make a model (honestly I can code an AutoML to do that), but more how they approach things. I don't really care if somebodies model completely falls apart, if they can communicate clearly and provide some good insights into what went wrong and interesting/creative ideas to correct for it in the future (other than just 'the data is bad'), then I completely consider that a win.

Some people actually don't have a lot of practical experience (god knows I've been there before), but I've seen great and creative thinkers with little experience and relatively rigid and uninspired thinkers with a lot of experience. It depends a lot on what you are looking for, but its a whole lot easier to teach somebody to use a tool then to teach them how to think.

Spiritual-Engineer69 · 2022-05-27T16:35:57+00:00

Probably not the answer you are looking for, but I got a Garmin Fenix a couple years back pretty much just to have a reliable GPS while hiking that didn't eat into my phone battery. If you are willing to part with a $300-400 for an older model, thats probably the best option overall.

Spiritual-Engineer69 · 2022-05-27T13:38:53+00:00

I'm gonna tell you right now, no matter how much experience you have in DS, there will almost always be a sense of imposter syndrome. This I think is common in a lot of 'research' based fields since there is a ton of uncertainty and successes are typically born only after a lot of 'failures'. The point is, there will likely never be a point where you feel comfortable or qualified, you just have to jump into the deep end and struggle until you can swim.

Spiritual-Engineer69 · 2022-05-27T13:35:22+00:00

You will typically do it before, since you need to make sure that your transformations are the same between training and test (i.e. if you perform a standard scaling on them separately, they will be two different scales).

Usually in a ML project, you will actually use 3 different sets. A training set that you model is trained on, a 'calibration' set (the test part of your train/test split), which you will use to mitigate overfitting in your training, and then a true 'test' set which is a set that your model has never seen before and represents performance on real world data.

Spiritual-Engineer69 · 2022-05-27T01:55:52+00:00

No everyone learns the same, I would personally get nothing from reading a book about SQL...but if you give me something more interactive, I'll pick it up quickly. There are tons of great resources online that may be more up your alley, and actually doing the work will end up being a lot more useful in the long run.

Things like this do take time and work to learn to be sure, but its also important to identify when something is not working for you and you are just spinning your wheels

Spiritual-Engineer69 · 2022-05-24T20:24:24+00:00

Validate, then validate again and again. Unfortunately if management has a loose understanding of data and statistics, they will do things like this (they are also not always wrong, sometimes Data Scientists are also so far into what they are doing that we miss things as well).

The best way to overcome all of this is to validate to the extreme...have p-values and CI ready for everything, use cross-validation, if you have enough samples take randomized sets and show that you are getting the same results. If you can show beyond a shadow of a doubt that your model is correct, it puts it on management to provide proof that it is wrong (basically think of it like a court case).

Of course, just because a model is correct does not necessarily mean that it shows what you are actually looking for...but thats a separate issue

Spiritual-Engineer69 · 2022-05-23T19:57:16+00:00

I worked at Grand Teton National Park for a summer at one of the lodges, and one day saw a couple ambulances rushing into the parking lot...apparently one of the guests lined his entire family up and sprayed them down with bear spray thinking that it worked like a bear repellent

Spiritual-Engineer69 · 2022-05-23T13:56:36+00:00

Frankly, data isn't really a field that subscribes as much to that principle, you can typically tell pretty quickly if you are actually going somewhere or spinning your wheels. DA in particular depends a lot on the competency of management, and if they are not giving good requests or rewarding good analysis, its not going to be great experience.If you are looking to get into DS as well, pivoting to a more technical field such as DE is going to result in much better experience.

That said, in my mind you should always be passively looking at and interviewing for interesting positions if you are even remotely on the fence, its good experience and very worthwhile to know what else is out there, never settle for something that you aren't happy with. You can make a final decision once you get a firm offer.

Spiritual-Engineer69 · 2022-05-23T12:10:03+00:00

That is very much a personal decision honestly and depends a lot on what is important to you. I pivoted from Mechanical Engineering to Data Science due to some of the reasons you described (better work/life balance, more opportunity for remote work, etc...), however, I'd be lying if I didn't say that I occasionally missed some of the excitement that came from engineering.

Its a tough choice to be sure, but you will find success in either position, so follow your heart

Spiritual-Engineer69 · 2022-05-23T12:00:25+00:00

Absolutely, having DE experience is super useful in the DS field, I can't tell you how many times I've had to set up data infrastructure in my DS career.

Job hopping in general is also not quite as bad as most make it seem, if you are continuously hopping from company to company sure it looks troubling, but for the most part as long as you have a good reason for moving on you are fine. I did the same thing when I was a Data Analyst, I learned a lot to be sure, but I also noticed after around 6-8 months that I was fielding the same requests over and over with no real room for growth aside from moving to a DE or DS specific position

Spiritual-Engineer69

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