Mike X Cohen PhD, Sincxpress Education

I don't know what's going on in this AI image.

But I do know this: Daily Data Challenge #25 is short and very practical for data science. You'll get to create a symmetric matrix and extract its unique elements.

Can you solve it in less than 6 minutes?
mikexcohen.substack.com/p/ddc-25-uni...

Awesome.

Here’s a picture of Thalorion The Destroyer reading my calculus textbook. I hope he likes it! Otherwise he might unleash doom on humanity.
www.amazon.com/dp/B0DX6BPPZ8

Interesting perspective. I think peer-review is imperfect but does more good than harm. I've published >100 papers and reviewed... dunno, many 100s of manuscripts. My thinking is that the incentive structure is the root of the problem, although I could be wrong. I agree with your suggestions though.

Fair point. I suppose the question is whether the entire system needs to be revamped (I'd find that unlikely to happen, given that too many people are too vested in it) or whether relatively small changes can have meaningful impact.

I'd love to see the evaluations in academia based on one paper every five years. Not a perfect solution, but it would increase scientific publishing signal-to-noise-ratio by encouraging researchers to put more effort into a smaller number of papers.

Mike X Cohen | Mike X Cohen, PhD | Substack Former neuroscience professor, current independent educator. I help people understand applied math and AI, machine-learning, deep learning, LLM mechanisms, etc. My motto is "you can learn a lot of mat...

Hehe, yep, although I'm not so active here. I'm mostly building up content (tutorial posts on data science and LLM mechanisms) on mikexcohen.substack.com.

Nice to hear from you, Luiz!

That was definitely part of my decision, although I wouldn't call it a "problem." More that I was (and still am) in an extremely fortunate situation, and decided to spend my time in a career that had higher positive impact for more people, and that was also more personally satisfying.

Thank you for taking the time to share you lucid and honest opinion.

Thank you kindly, Thomas. My feelings, reactions, and motivations are definitely not unique, but ex-academics have an unfortunate habit of reticence.

DDC-23: Distributions of MNIST pixel values A data challenge a day helps you master machine learning

Karl Gauss (yeah, *that* Gauss) sent me a fax this morning to say that he really enjoyed working through today's Daily Data Challenge.
mikexcohen.substack.com/p/ddc-23-dis...

You earned them.

That is a fantastic title and topic. Congrats!

Why I left academia and neuroscience Don't worry, this isn't yet another story of rage-quitting.

Why I left academia and neuroscience.

This post on Substack has gained a lot of traction. I think many people identify with it.
(Most of my posts are technical tutorials on machine-learning and LLM-mechanisms.)
mikexcohen.substack.com/p/why-i-left...

Thank you, Felipe :)

YouTube video by Mike X Cohen Daily Data Challenge 8: Test for Pythagorean triplets

Daily Data Challenge 8: Test for Pythagorean triplets
A data challenge a day helps you master machine learning.
More exercises and solutions at mikexcohen.substack.com

youtube.com/shorts/LlqS2...

Confidence intervals 2/3: bootstrapping methods Learn computational statistics in the second part of this three-part series.

Bootstrapping: because sometimes asking “what if?” 10,000 times is a valid math strategy.
open.substack.com/pub/mikexcoh...

genAI never fails to deliver the laughs.

Daily Data Challenges are going strong.

Today's challenge is to create this beautiful graph using numpy and matplotlib. Can you do it?
mikexcohen.substack.com/p/ddc-18-err...

This is not a post Will pipes exist in 100 trillion years?

This is not a skeet.
mikexcohen.substack.com/p/this-is-no...

Have you done your Daily Data Challenge?
mikexcohen.substack.com/p/ddc-8-test...

People talk a lot about GPT5 and hallucinations and trust and so on.

But let's not forget that GPT2 is the ultimate arbiter of truth and science.

Proof of my claim? This zinger from GPT2.

Wanna explore GPT2's wisdom in your own private Python session? mikexcohen.substack.com/p/lessons-on...

GPT2 is hilarious.

LLM breakdown 1/6: Tokenization (words to integers) Large language models can't read; instead, they are given numbers that come from text.

Dear bluesky neuroscientists: You should pay attention to the field of LLM mechanistic interpretability.

Not because LLMs are like real brains (they are absolutely nothing alike), but because mech interp analysis methods would be useful in neuroscience.

Start learning here: tinyurl.com/48pum4pb

One of my fav quotes: "The way you do anything is the way you do everything."

The problem with these pithy faux-philosophical quotes is that they don't stand up to scrutiny. For example, I definitely do not pick my nose with the same rigor, depth, and intensity with which I write 600-page textbooks

Can you code the Fourier transform from scratch?

I bet you can. Spend 20 minutes on the Substack post, and you'll learn everything you need to understand and code the FT in Python.
mikexcohen.substack.com/p/the-fourie...

Confidence intervals 1/3: interpretation and equation Start building confidence about confidence intervals in the first of this three-part series.

Do you have enough confidence?

I am, of course, talking about confidence intervals, the statistical measure of uncertainty around a sample characteristic like the average or correlation.

Here's my latest series on Substack about confidence intervals: mikexcohen.substack.com/p/confidence...

Daily data challenge. 10 minutes a day to improve your coding, data science, and visualization skills.

open.substack.com/pub/mikexcoh...

Good for you! Keep it up.

Happy teacher's day (in India)!