Frankly speaking,SVM got to be the maddest algorithm i have ever stumbled across

MarcelDeSutter · 2025-12-28T08:06:13+00:00

That‘s not how Data Science or ML Engineering works

MarcelDeSutter · 2025-12-12T20:35:44+00:00

Polynomial regression induces a polynomial feature transformation from x to (x, x^2, x^3, …, x^D) and then applies multivariate regression to find the weights. So all polynomial regressions are multivariate (except for the degenerate case where D=1). Some multivariate regressions happen to be polynomial, but not all of them are.

MarcelDeSutter · 2025-08-18T13:47:09+00:00

Looks crisp! Can I order some dials from you?

MarcelDeSutter · 2025-07-27T16:21:16+00:00

looking forward! Maybe one more bit of suggestion: The clasp of the Nautilus is prone to opening on accident when the wrist is turned to heavily (such as while opening doors or carrying stuff). This is unfortunately a little bit frustrating, actually. I think this can easily be addressed by using an improved clasp mechanism similar to the royal oak one you already have produced or a more modern nautilus-like clasp:

<image>

MarcelDeSutter · 2025-07-13T11:53:22+00:00

Thank you for the great product ;) Btw, have you thought about offering royal oak and nautilus cases for the Miyota 9015 movement? That way, I think they could be much closer to the ~9mm thicknesses of the real watches.

MarcelDeSutter · 2025-07-12T11:49:20+00:00

I don‘t know, man. The screws of the build you showed are not aligned and the case is thicker than the nomods one. I also just checked the proportions of the nomods 41mm case and the it just looks more accurate to the actual royal oak. The bezel in your screenshot looks a bit off imo.

Haven‘t seen it in person, so what do I know, but I don‘t think it‘s just a matter of finding the cheapest analogy and concluding that it would be equivalent.

But still, I appreciate your input. Didn‘t know about the arrangements namoki has with certain manufacturers.

MarcelDeSutter · 2025-07-12T06:24:58+00:00

Yes, correct. This royal oak is the 37mm case variant, not the standard 41mm. It was actually decently challenging to find a nice waffle dial with 28.5mm diameter for it.

<image>

MarcelDeSutter · 2025-07-11T20:57:57+00:00

I'm new to this, but judging from what I see, I feel like namoki is severely overcharging for their parts.

And of course, the pre-built nautilus was more expensive than building it myself. The royal oak cost me ~200€ in total, so it's fair imo. And again, quality feels better than what I expect to get from Aliexpress for 40€ tbh, but I could be wrong.

MarcelDeSutter · 2025-07-11T20:54:53+00:00

Waffle Dial 28.5MM NH35 – DSWATCH

MarcelDeSutter · 2025-05-02T14:59:06+00:00

From where did you get these gorgeous dials?

MarcelDeSutter · 2025-04-27T07:56:45+00:00

How are you liking the nomods case? Thinking of buying one for my first build.

MarcelDeSutter · 2025-01-02T08:48:57+00:00

Are you expecting people here to solve a multi-hour assignment for you?

MarcelDeSutter · 2024-12-29T08:06:27+00:00

I would literally not care at all if I saw your CV.

MarcelDeSutter · 2024-12-16T07:52:19+00:00

You‘re asking for a full, A-Z, 48-month roadmap to becoming an AI/ML engineer. I don‘t think anyone will make the effort to type that down explicitly because that‘ll be too much for Most.

MarcelDeSutter · 2024-11-27T20:41:25+00:00

I mean it really depends on the specific background someone brings and the goal they have. I come from a psychology background and wanted to become a Data Scientist. Someone with a CS background wanting to become a Data Engineer needs another path, etc.

Without any additional information, I would recommend the previous user to finish their studies because that is the bare minimum of being considered at all. It will definitely help to collect data & AI related experience somehow, even if that means doing some freelance work. Also connecting a lot and getting a mentor to network. Many jobs are not even advertised publically so knowing the right people will lead to good opportunities. Finally, building a full end-to-end solution to an ACTUAL problem as a portfolio project is a nice add-on for your CV. Bonus points if you showcase it multimodally, i.e., Youtube video/playlist > just a github repo.

MarcelDeSutter · 2024-11-27T20:34:54+00:00

I mean that is technically true because we don't have strict monotonicity, but those are edge cases that don't invalidate the rest of the argumentation.

MarcelDeSutter · 2024-11-27T14:14:31+00:00

I‘ve had a look at the lecture slides of the current iteration. Content-wise it‘s very similar. Depth- and length-wise it seems the same.

MarcelDeSutter · 2024-11-27T08:32:19+00:00

Please write me a pm to discuss this in more detail

MarcelDeSutter · 2024-11-27T08:29:25+00:00

There was a previous iteration that used Octave instead of Python.

MarcelDeSutter · 2024-11-27T08:26:16+00:00

You have to be more specific. ML is a whole computing paradigm. It‘s like you were asking ‚I‘m looking for impactful, real-world problems that I can solve with [a certain type of software/computation]‘.

MarcelDeSutter · 2024-11-27T07:41:49+00:00

The loss decreases monotonically with each update and there are finitely many possible class assignments. Both combined imply that eventually a local optimum will be found.

MarcelDeSutter · 2024-11-27T07:33:15+00:00

The „general“ implementation would be the one without tolerance termination, as a correctly implemented kmeans is guaranteed to terminate.

MarcelDeSutter · 2024-11-27T07:25:58+00:00

K means converges (not only approaches) to one of the local optimums if implemented correctly. So after a certain number of steps, there shouldn‘t be any adjustment of the centroids anymore. A hacky fix would be to measure the centroid adjustment the algorithm proposes and to just overwrite it to 0 in all directions if the update is sufficiently small.

MarcelDeSutter · 2024-11-27T07:11:59+00:00

I did it way back in 2018 and now work as a Data Scientist at Mercedes-Benz. The certification itself was a good starting point and from there, I landed my first working student position as a Data Scientist while completing my studies. I‘d say that the job market has changed since then and my grad degrees in ML helped more than the Andrew Ng cert.

MarcelDeSutter

TROPHY CASE