id_ris

One idea I've been using recently is to start writing unit tests around a piece of code or functionality as I'm trying to use it. That technique narrows the scope to a single thing, and I'm forced to be explicit about what I expect. That and reading the source code are my gotos.

There is no good reason to mimic matplotlib's API except that everyone knows it.

Did you consider creating a backend for Matplotlib which rendered to ascii?? That way a matplotlib user could simply switch backends when on the terminal, and then switch to something else when the execution context changes. I don't know if that's even feasible, but that was what I first this was when I saw plt.

How are people accessing GPT3? Is there a website, code repo, api... or do some select few have access?

None of these points address the hardest parts of buying lumber for a beginner. The hardest parts are in no particular order

* knowing the maximum dimensions you can fit into your vehicle. Are you sure it'll fit in through the door or hatch and you'll be able to close it?

* knowing what cuts you can make at home, and which ones you need to have done at the lumber yard / big box retailer.

* if you need cuts done at the store, does that store offer that service? For example the Menards I shop at has an amazing selection of wood, but they won't cut any of it for me. The Lowe's has a smaller selection, but they do cuts for free.

* if you're having cuts at the store, make sure the saw is working before doing the hard work of choosing your lumber. Too many times to count I've spent 30 minutes getting all the pieces loaded on the cart and then noticed the "Out of Order" sign and had to leave empty handed.

* are you strong enough to lift the piece? Plywood comes in 4 foot by 8 foot sheets, and they can be heavy and awkward to move. A store employee can help you, but at some point you're on your own and will need to do it yourself, have some help, or fashion some tools to assist you.

* For cuts at the store, do you know what dimensions to tell the employee to cut at? Store cuts should be considered rough cuts than you true up later on. Make sure you account for this when dictating the cuts.

* Lastly, just assume you'll make mistakes early on. Luckily construction lumber in the US is pretty cheap, so you can afford a few lessons.

Is it not available through 'AVCaptureDepthDataOutput`? My understanding is that depth data is a separate channel stored in photos.

The biggest drawbacks of Swift are the legacy relationships it has to the Apple ecosystem.

Yet swift is open source, and Apple and the community can fork it if they so choose. This is great news for me personally as an iOS developer and an ML noob who doesn't want to write Python. I can't comment on Julia because I have no experience with it, but I applaud the efforts to build the Swift ecosystem to challenge Python.

I think a lot of the criticisms so far are that it's early days for Swift in ML, and that's one point the author is emphasizing.

I'm an iOS developer deeply familiar with Swift and on the path of learning ML. The irritation with "import Foundation" is understandable. Foundation is, wait for it, the Foundation of Objective-C programming and development for the iPhone. It's a library Swift makes use of and needs to inter-op with due to legacy concerns for iOS and Mac developers.

It's not an inherent part of Swift the language, and efforts like those at Google and the open source development of Swift can develop more modern and suitable replacements for those libraries.

I like python, but man I really don't want to make large systems in it. Swift is a great language, and imo the biggest thing holding it back is that it's intertwined with a lot of Apple code. But it doesn't need to stay that way, and for that reason I applaud the efforts to move it beyond just an "app creation" language.

Very nice writeup. It's fun to see linear algebra out in the wild.

There is a lot of excitement around machine learning and AI and there is not a proportional excitement for the math that underlies the theory.

In a lot of content that teaches machine learning/AI, the linear algebra substrate of it is given short shrift.

The consumers of that content infer that the backing mathematics is easy or unimportant, while the creators of the content are not actually implying that, but just want to move on to what the audience came for.

I'm not an expert in machine learning so I can't say whether you can get by without a strong understanding of linear algebra, but my intuition answer is no you can't. Beside that, I enjoy the math for its own sake so I'm happy to trudge through the textbooks.

And no, I don't think the blog post makes any claims that it is a subsitute for taking a course in linear algebra.

I recently finished going through MIT OCW's linear algebra class from Gilbert Strang. Without the struggle of doing the assignments, reading the text, and watching the lectures, I don't think I would have ever learned the content. While content like this and that from 3blue1brown are commendable and useful, it simply would not have lodged the ideas into my head.

Now that the ideas of things like vector spaces, norms, orthogonality, rank, basis, etc are nearly second nature, the concepts are useful as I study other branches of math which would feel impenetrable otherwise.

YMMV, and if you can learn from condensed materials go for it, but I might be too dumb for it work lol. I think the real benefit accrues to the author who had to work out how to teach these concepts to others.

is there anything to verify that this isn't clickbait to get addresses for an email list

Dr. Rhonda Patrick. she has a website and podcast

just when I thought I was becoming competent at shell scripts, a post like this reminds me of all the issues that I hadn't even known existed.

What do you want to do? Do you want to be the lead person adding automation to the analysts jobs? It sounds like you could catapult yourself up a few rungs on the ladder and have a staff working with you to improve the analysts' jobs with automation tools.

You do not explicitly state whether you created this software on company time or with company equipment. If you did it with personal equipment, I'd try to sell it to them. If that's unworkable, you could give the software to them and then offer to be their consultant to keep it working and to add features, at a hefty salary bump.

Ultimately we need to know what you are trying to optimize for: positioning in the company hierarchy, money, ...?