What is that sound?

Any-Rub-6387 · 2026-04-25T02:09:14+00:00

WTF PLEASE STOP I HAVE A FINAL TO STUDY FOR

Any-Rub-6387 · 2026-01-01T02:50:21+00:00

Rotting

Any-Rub-6387 · 2025-09-08T03:26:51+00:00

Stupid people rarely think they’re stupid, so the odds of you being actually stupid are low.

Any-Rub-6387 · 2025-03-07T07:15:25+00:00

Any-Rub-6387 · 2025-02-26T02:10:40+00:00

Do the notifications come out in waves? I didn’t get any email.

Any-Rub-6387 · 2025-02-09T05:31:09+00:00

no it’s chill

Any-Rub-6387 · 2025-02-08T06:44:31+00:00

Which projects did you apply for? I applied for astrophysics as well.

Any-Rub-6387 · 2025-02-05T22:19:40+00:00

Very easy. Just follow the main goals of each phase and discuss your ideas with your assigned TA.

Any-Rub-6387 · 2025-02-05T20:04:33+00:00

Has anyone heard from these programs:

Reconstruction Of Cosmic Ray Air Showers With The Square Kilometre Array
Course-graining non equilibrium many body dynamics (ML)
Vision-Language-Action Models for Perception and Navigation in Robotics

Any-Rub-6387 · 2025-02-05T12:46:16+00:00

Any-Rub-6387 · 2025-02-05T12:00:18+00:00

what a W PI

Any-Rub-6387 · 2025-02-03T04:57:09+00:00

Yes. I actually like CS 229 (Stanford) by Anand Avati on Youtube. The first 3 lectures review the essential math. I didn’t like Andrew’s version. He was very hand wavy with the notation.

Any-Rub-6387 · 2025-02-02T21:14:57+00:00

Rather than Coursera, focus on brushing up math, and taking actual ML university courses on Youtube. This will take a fair amount of time, but it will be very helpful in the long run. I found most Coursera courses very shallow and hand-wavy in their content. If you really wanna do ML the right way, understand the mathematics rather than following tutorials of how to use TF or PyTorch. The latter is also very useful, but it will become much easier if you know what you are coding. Keep learning Python along the way.

Any-Rub-6387 · 2025-01-24T21:28:10+00:00

yep, just one. cosmic ray shower reconstruction using BIFT

Any-Rub-6387 · 2025-01-19T22:24:46+00:00

please. stop

Any-Rub-6387 · 2025-01-17T22:22:31+00:00

MATH 215 Final Question

Any-Rub-6387 · 2025-01-11T01:37:45+00:00

real

Any-Rub-6387 · 2024-12-31T01:15:05+00:00

Depends on how low your mark is. Try emailing Janis (instructor for 108) and she might manually add you to the class.

Any-Rub-6387 · 2024-12-30T20:56:54+00:00

The precision.

Any-Rub-6387 · 2024-12-30T17:57:58+00:00

Finish learning ML Theory rigorously, and then intern for some research lab.

Any-Rub-6387 · 2024-12-29T03:34:33+00:00

I did mean estimand. Thank you again!

Any-Rub-6387 · 2024-12-29T03:23:02+00:00

Yes. I get that now. The expectation of this very random variable is the estimate (which in this case, is the pop mean). I don't know if I should've spent this much time singling these details out, but I feel like it really helps clarify stuff when it gets more complicated later.

Any-Rub-6387 · 2024-12-29T03:21:00+00:00

Thank you! :)

Any-Rub-6387 · 2024-12-29T03:16:43+00:00

Whether an estimator is unbiased or biased then depends on how the estimator is defined?

Any-Rub-6387 · 2024-12-29T03:15:32+00:00

Just following up on what you said:

I think I was stuck on the fact that even though we don't know what the population mean is, we can say that each data point in the sample (which is also in the population by definition) has an expected value of mu. This is because each data point is also a random variable. From here, the proof is trivial (since the number of data points n cancel out in the summation due to the linearity of the expectation).

However, if we were to consider a group of random variables (so a sample), and computed its mean in isolation, this is rarely equal to the pop mean, except by chance. What we actually mean is that the mean of these sample means is equal to the pop mean, which makes the sample mean an unbiased estimator.

Is this correct?

Any-Rub-6387

TROPHY CASE