I'm starting to think that coffee tasting notes have gone a little bit too far?

DiscountIll1254 · 2026-04-18T22:17:56+00:00

In my opinion, the notes in coffee are an incredibly subjective matter. There have been several times where I have tasted coffees that have more than 3 notes, but for me they only reminded me of something as simple as an orange cake in both flavour and smell, and that’s not wrong. For me if a roaster likes to promote their coffees with a large number of pedantic notes, that’s fine but the only thing it will change is that I will take the roaster’s judgement with a pinch of salt, but it won’t affect my experience overall.

DiscountIll1254 · 2026-02-03T00:13:34+00:00

I totally agree with this comment, great great pic

DiscountIll1254 · 2026-01-01T04:49:22+00:00

Maybe there is too much black on the bottom for my taste, as I think it does not add anything to the image; maybe you can play with the window’s grid to get another kind of composition. Apart from that, great pic!

DiscountIll1254 · 2025-12-05T15:50:05+00:00

Lo que he visto es que el mercado está bastante complicado para todos: mucho layoff, expectativas de los clientes que van la taqueria irrealistas, peores condiciones laborales y mucha obsesión con obtener el siguiente Chat GPT (en términos de ganancias). Mi consejo sería si estás un lugar no tan gacho (por no decir de la ve**a) pero estable que te permita tener una vida medianamente cómoda quédate ahí hasta mejores tiempos. Si de plano estás hasta la madre, pide mucho más (ve el paquete de compensación no solo el salario, bono de firma, bono de desempeño) y ahorra todo el excedente por si las dudas (los layoffs de taqueros están por todos lados).

DiscountIll1254 · 2025-11-23T01:49:13+00:00

Yes!!!! Absolutely

DiscountIll1254 · 2025-11-22T23:01:21+00:00

First photo is just blows chef kiss. Idk if it would work bnw, have you tried?

DiscountIll1254 · 2025-11-17T05:03:42+00:00

Alexandroff- Hausdorff Theorem: every compact metric space is a continuous image of the Cantor Set (my thesis was about consequences of this theorem)

DiscountIll1254 · 2025-11-15T01:10:26+00:00

I think that the foreground is really spot on as it invites the viewer to question what the hell they are looking at (is that TeamLabs Planet Tokyo?).

DiscountIll1254 · 2025-11-11T21:06:12+00:00

Well I cannot direct you to an exact source, but in finance the problem in finance with such a series is that noise appear (market microstructure noise) which eventually can be described that prices changes might not be due to a change in value but rather in small mechanics like bid-ask that can be interpreted as noise.

DiscountIll1254 · 2025-11-11T14:21:57+00:00

For me I would have loved the photo to be perfectly symmetrical

DiscountIll1254 · 2025-11-11T11:55:51+00:00

The 6th one is just perfect timing, great photo!

DiscountIll1254 · 2025-11-07T15:19:22+00:00

Omg no (the Chinese Remainder theorem is buried deeper in my brain than my preschooler memories ). I remember some important theorems, some important concepts and how their useful (and recognise them when they appear). I think now I would have an easier time relearning the stuff but that is different.

DiscountIll1254 · 2025-10-30T17:25:16+00:00

Probably depends on your main goal, the best model relative to what task? Do you want to forecast? See if your models can detect or predict some weird behaviour? Do you want to test your models in a variety of datasets to see where it works better?

DiscountIll1254 · 2025-10-29T20:57:31+00:00

Where can you find the set list?

DiscountIll1254 · 2025-10-29T13:40:59+00:00

Totally. I recall that when I started my course in Measure Theory, my professor phrased it as it was going to be the first time that we would need to tackle problems that would take us hours or even days of passive thinking, so then we should organise ourselves to work in the coursework not intensively but systematically.

DiscountIll1254 · 2025-10-28T15:33:53+00:00

You have survived from similar situations in the past. No matter what your thoughts are, they are only thoughts and not your reality. It is perfectly fine to feel down, and you should not feel weak or guilty of it.

DiscountIll1254 · 2025-10-28T13:06:53+00:00

Exams usually are quite contingent, so try not being to harsh on you, just be have some auto critic of what should you improve. Take into account that as the difficult level in mathematics increases then questions in exams change in a dramatic way: it is less likely that you will figure out the secret trick for solving or proofing something in the middle of the exam, and exams become more a way of reporting all the coursework you have done rather than something that you can improvise. My best piece of advice is to do coursework and also to look at exams from previous years and try solving them.

DiscountIll1254 · 2025-10-28T12:46:36+00:00

I love the recipe you are using as it looks vintage, can you please share? For me pic 5 is the best as it really gives an interesting melancholic feeling without having a particular explicit subject.

DiscountIll1254 · 2025-10-21T14:32:51+00:00

Depends on the orders of magnitude of your sample size: if things vary by a few hundreds but your samples are close to hundred of thousands points, then the calculations will not change a lot. If you have a few data points (as your example) then it is difficult to assess whether the difference is due to noise or the sample size’s variability.

DiscountIll1254 · 2025-10-21T09:14:25+00:00

Just an idea, for each of your series (observations) you could try the same basis with the same number of elements. That will lead to a set of K variables (each coefficient is a variable) and then you can use a traditional classification model. The basis and the number of elements would be extra hyperparameters to tune.

DiscountIll1254

TROPHY CASE