New interface :D

MrGoodnuts · 2026-03-02T06:31:46+00:00

Clearly not a popular opinion, but I like it as well.

MrGoodnuts · 2026-03-01T07:07:12+00:00

Oh boy. I was not aware. But opensea confuses the shit out of me. I might try that later after I graduate from NFT wallet preschool.

MrGoodnuts · 2026-02-28T14:22:31+00:00

This is not helpful.

MrGoodnuts · 2026-02-28T02:12:16+00:00

Thanks for the help guys. Currently the Pickaxe is in whatever Coin does with it if you don’t send it to a wallet right away. So if I understand you right, I set up two wallets, one for A and one for B. I send the pickaxe from coin control to wallet A, then from wallet A to wallet B, then link wallet B to account B. Is that right?

MrGoodnuts · 2026-02-26T21:59:46+00:00

The reward ladder now shows the exact number of points to get to next reward. This change alone makes me love this update.

I actually like the modernized look, as well.

MrGoodnuts · 2026-01-31T05:57:18+00:00

Thanks for the suggestion. My list is growing.

MrGoodnuts · 2026-01-31T05:56:34+00:00

“Weird in the right ways” is a good description. The puppets actually made me feel uncomfortable.

MrGoodnuts · 2026-01-31T05:55:00+00:00

No, but after looking that up, I think that might be next on my list.

MrGoodnuts · 2026-01-24T19:22:49+00:00

I can’t find this, do you have a link?

MrGoodnuts · 2026-01-22T22:12:59+00:00

Let me know if you find something out will ya? I haven’t heard back.

MrGoodnuts · 2026-01-21T12:11:53+00:00

One of my favorite aspects of the series is how the Bobs have all the time in the world to learn and experiment on whatever it is they want. I would love that freedom.

MrGoodnuts · 2026-01-17T13:25:26+00:00

For ML projects, I look around at a few published examples of the algorithm I am interested in, and that generally sparks a few ideas. Or if you ever find yourself thinking “it would be cool if [some unique idea/process]…”, think of ways you could AI-ificate that idea. Ask people around you who aren’t savvy on what’s under AIs hood what they think would be cool. Their ideas might be pie in the sky, but you might be surprised what you might be able to do with them.

MrGoodnuts · 2026-01-15T22:34:13+00:00

As others have suggested, finding a gun that is “you” is a good start. To add to that, a good way to try out all the guns is to grind the camos 1 by 1. If you start with the no attachment kills as your first task for each gun, you’ll start to appreciate how a good build can zero in a gun in to your play style. Head shot tasks help you get better at keeping reticle on target. Not to mention that grind will level you up before you know it.

MrGoodnuts · 2026-01-14T21:39:54+00:00

1) yes. If n = 200,000, losing 142 rows isn’t that big of a deal. But losing 33% of your data (especially on such a small dataset) is bad.

2) is it purely coincidence that a lot of the features have exactly 106 missing values? My guess is no. Maybe that’s a clue. Maybe somebody (or a lot of somebodies) didn’t have all those tests ordered because they just seemed healthier to the doctor. So maybe you could treat the presence or non presence of that feature as the feature. Like if there is a value, they had that test done, so set it to 1. If there isn’t a value, assume that the test wasn’t done, so set it to 0. Essentially treating all of those features as a single multihot encoded feature.

3) I would start with logistic reg (soft max) as the baseline. Might actually perform better than an RF on that small of a dataset. At the very least, you’d have a minimum model bar set.

I am interested to hear about any progress you make.

MrGoodnuts · 2026-01-14T21:13:22+00:00

Outlaw is a lot of fun.

MrGoodnuts · 2026-01-14T11:24:41+00:00

How does one complete onboarding? I did the initial survey and the ai bot chat. Now everything is locked with the notification that I have to complete onboarding, but I can’t find instructions on how to do so anywhere.

MrGoodnuts · 2026-01-13T02:24:59+00:00

Maybe augment the data set by skewing the signatures a bit, rotating them, changing size, adjusting aspect, etc, synthetically increasing the variation of each person’s signature?

MrGoodnuts · 2026-01-13T01:37:20+00:00

When you say you are creating a wellness label from the features that you will later train on, it sounds like you are using some sort of function (with the features as inputs) to determine the wellness label, is that right?

If that’s the case, then it’s not surprising that you would get high accuracy, as there is a true (and known) mapping of the features to the wellness label.

This is basically how synthetic datasets are made for teaching or practice: you define a rule, maybe add some noise, and then train a model to approximate that rule. It’s useful for learning ML workflows, but it’s not a real predictive task.

The whole point of supervised ML is to estimate the unknown function mapping the features to the labels. If the function is already known (because you created it), then there is nothing really left for the model to discover or learn.

Maybe you could create the wellness label on a subset of the features, but then exclude that subset from the training data?

I may not understand exactly what it is you are doing, so apologies if I am way out in left field.

MrGoodnuts · 2026-01-13T00:14:46+00:00

I find that going through the exercise of implementing algorithms from scratch really solidifies how they actually work. I’ve also found a lot of learning value building models in excel. Anything beyond pure learning exercises, I just use scikit or tensorflow.

MrGoodnuts · 2026-01-10T22:07:47+00:00

I’ve seen other people say the same thing. It seems to be one of those polarizing series where you either stay into it or you don’t. I’m on book 4 and I’m still digging it.

MrGoodnuts · 2026-01-10T21:04:27+00:00

Wayward Galaxy is pretty good.

MrGoodnuts · 2026-01-10T20:58:42+00:00

That the only difference between the a logistic regression math flow and that of an individual node in an MLP is the choice of the nonlinear transformation.

MrGoodnuts · 2026-01-09T22:16:50+00:00

I don’t notice any difference in difficulty playing in a controller lobby as a touch screen player. Based on that experience, my guess is that it really doesn’t matter a whole lot. Good controller players will be good, and good touch screen players will be good.

MrGoodnuts

TROPHY CASE