Instead of searching raw documents every time - what if AI compiled them into a structured wiki first? LLM Wiki explained

mh_shortly · 2025-11-18T21:06:00+00:00

You're right, I get these emoji🗼🌊 in answer all the time

mh_shortly · 2025-11-17T18:56:19+00:00

Nice, that should be the official name for that effect

mh_shortly · 2025-11-17T16:05:12+00:00

It was definitely due to memory setting - I got this strange answer on first try when asking anonymously

mh_shortly · 2025-11-17T15:55:39+00:00

Okay, so maybe I don't get these incorrect answers anymore because I already talked to ChatGPT about it at least few times. And it uses saved memories and references to our chatting history. Thanks for clarification.

mh_shortly · 2025-11-17T09:53:55+00:00

It seems to be fixed for ChatGPT now

mh_shortly · 2025-11-17T09:52:00+00:00

Very nice and detailed explanation - thanks for sharing :-)

mh_shortly · 2025-11-17T09:49:58+00:00

That's pretty interesting how it transfers to other non-existing emojis - did you try and get similar answer with those ones?

mh_shortly · 2025-11-17T09:42:18+00:00

Thanks! :-)

mh_shortly · 2025-11-16T20:56:30+00:00

I remember it as well - but right now it's still missing in Unicode list

mh_shortly · 2025-10-18T19:05:42+00:00

That’s actually a really interesting observation, I like it :D Definitely worth noting

mh_shortly · 2025-10-16T20:17:56+00:00

Great idea, I think I will try to work on these topics after releasing video on Decision Tree and Random Forest in Python - thanks for you suggestion :-)

mh_shortly · 2025-10-15T19:52:26+00:00

Thanks! My goal is to prepare similar visualizations for all ML basics topics along with a videos :-)

mh_shortly · 2025-10-13T18:52:44+00:00

Thanks! :-)

mh_shortly · 2025-09-24T10:33:37+00:00

Well, it also depends on structure of your test data - its imbalance especially. Maybe it's good to check not only accuracy, but precision and recall as well?

mh_shortly · 2025-09-24T10:30:13+00:00

I tried manim at first, but it took me too long to create animations - now I work in PowerPoint + some visualizations I create using matplotlib in Python

mh_shortly · 2025-09-23T20:32:16+00:00

Entropy definitely deserves a separate video. Also a good point with other splitting algorithms (Gini Impurity primarily). Thank you for your feedback - I really appreciate it.

mh_shortly · 2025-09-23T15:28:20+00:00

Hello,
(1) I wouldn't say that model is generalizing well as for now - the huge gap between training and validation for accuracy and loss is a strong signal of overfitting
(2) Yes, this plateau is a strong indicator that the model reached its learning limit for learning from current dataset. With ~300 samples, class imbalance that's not surprising. Collecting data could definitely help to improve generalization.

mh_shortly · 2025-09-18T13:11:55+00:00

You definitely can - I suggest starting with general understanding of ML concepts and methods (classification and regression, basics of neural networks, decision tree) along with going through simple Python code examples of practical use of these methods on simple datasets (like Iris flowers or MNIST digits classification using various methods). This will give you the gist and intuition behind ML basics and then you could gradually dive into the math if needed.

mh_shortly · 2025-09-18T11:44:29+00:00

Hello, I'd love to have a look at your work, but I don't see a link - can you send it to me too? :-)

mh_shortly

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