Video

Man, can you make your accent smoother

Guru of Fundamentals. I can't resist subscribing to your channel and watch all of your videos. The way you explained Chain Rule : the logic behind it is awesome. I am trying to visualize the Quotient Rule of Derivatives in your way. A good Teacher always makes you THINK 🙏

Thanks a lot for this intuitive video, I enjoyed to watch this, specially in dot product, I was confused why we use kernel trick in SVM and now I know it.

Is it only me or the background music selection is inspired by 3blue1brown just as well as the visuals and approach overall? For some reason I'm flashing back to 2021 when I binge-watched 3b1b, just by listening to the background. I know it's generic but not in sci-pop apparently.

what does "fourier transform is completely blind to time" even mean?! you can recover the original signal doing the inverse fourier transform: no loss of information

I'd click 'thumb up' a thousand times if I could, thanks a lot Artem!

спасибо, Артем)

Such a good video. Have liked and subscribed! I love the Curve Fitter 6000 machine in the animations to explain these concepts. Most textbooks are just too abstract and confusing but you have done a great job.

So, hard links exist in our brains.

Well, now I know how Trauma works. So, dealing with it as early as possible helps in the person not being able to develop it over time.

Your approach to trading is truly impressive. Thank you for teaching me so much!

Absolutely one of the best videos explaining data points and regression formulas I have ever seen. Amazing work

This is the best CZcams video I have ever seen. You explained everything masterfully! Thank you for giving my curiosity a vision, I’m so excited to explore more.

Thanks for this video. It's very educational and as said before here in the comments an easy-to-follow instruction to start with Obsidian and Zettelkasten. Also - I simply love the name you gave yours.

Very nice explanation.

The best explanation of machime learning i have ever seen on you tube ,amazing work .thank you👍

Best video I've ever watched about Obsidian. I'm really thankful for this content

The outro music 🙏🏻🙏🏻🙏🏻

Thanks for such a this amazing content

This video is actually the best I've found

tmi

MY DOUBT: Is it guaranteed that the loss function will always be a smooth well like hypersurface? Couldn't it have many local minima where we can get stuck?

Thank you for this video!

Why not the Hopf Vibration instead of a torus?

After getting a 10/10 in Calc II (Calc II is mutlivariable calculus in my country) I feel proud of myself for being able to skip most of this video because I immediately thought of the method and I was correct (even though I didn't learn it in uni)

How’d you do the animations?

Too long doing basic math - not what the title said - turned off.

can anyone please help explain why did he raise x1 to the power in 28:40 ?

Can you talk about attention mechanisme ?

Продал родину за бургеры

Its really too much helpfull to visualize and understand each and every thing

The replay goes in reverse order to allow back propagation.

Really good that you’re covering these foundational concepts of NNs. Cross-associative NNs, auto-associative NNs, and unsupervised learning are big missing pieces in today’s NNs.

This was one of the good oness. I really loved it and hope part 2 comes out sooner. Keep up the amazing production sir.

That excitatory and inhibitory connections remind me of statistical correlation function

Isn't the 2nd law of thermodynamics more directly linked to entropy? Is there an analog for entropy in the associative memory network?

Reminds me of gradient descent

The protein example got me thinking. Is there only one unique folded configuration of the lowest energy? Can there be multiple stable comfiguration anyway, and transitions between them?

This is really cool! Thanks for your work Artem!

This video is a gem.

Hello. It's been long since you last uploaded the last video. I hope you are well. Best videos, bro. Keep them coming 🎉

Thank you Artem Kirsanov for the incredible tool, I presented it to the entire physiological sciences department at my university

Man, you really nailed it, especially the Computational Graph and Autodiff part. I heard so many times about them in lectures on Stanford and others. However, this was impressive.

Good stuff!

чё за песенка там на русском?

Fabulous, bravo

Anyone else following the series? What do you think so far?

Artem!!! Is there any chance you've visualized feature engineering concepts like PCA, IPW, or weight of evidence encoding? Others have done it but your explanations are par-none ❤

Thanks!

Thanks!