Відео

Anyone else watching this because of the KAN paper that just came out? lol Great video! 👍

help me a lot, can't wait to see more

can u make a video about Piecewise Affine Transformation . i made some diy book scanner .i have some curved pages while i scann . this issue is something that can be solved with a programm called abbyfinereader and the command straighten text line . but i am trying to correct it with python.

come back :(

Excellent explanation. Thank you.

these videos are gold!

hats off.

grateful

you are the best. I watched many vids but that is the only one makes sense.

excellent explanation, thanks

very good mate.

hear me out. it'll be "Interpolation in 2.5 minutes" if you put the playback speed on 2x

Excellent in every respect. I read the remaining comments agreeing with most of them and ticking the like thumbs to save me repeating what they have said. Thanks a lot.

Finally! Someone who knows how explain complexity with simplicity.

Excellent

Thanks, what a video, in 8 minutes I have learnet so much, and very well explained with graphics indeed.

Beneficial

This was so surprisingly great :3

This is really awsome! It's the best video that explains DRL in such an easy to understand way!

how many layers should such network have

The third interpretation for mirror reflection is so funny out of context

I totally love the way you explained this :)

I've watched a bunch of different videos about Ray Tracing and Path Tracing and they all say that the rays fly out of the camera and reflect off the surface, the difference is that in Path Tracing many rays will reflect in random directions, while in Ray Tracing a single ray will reflect and fly directly to the light source. This raised a lot of questions in my mind, how do reflections, shadows, transparent materials, etc. work in Ray Tracing, but no one in their videos even thinks about it, they just reflect a ray once and that's it. I finally found this video that explained literally everything and answered all my questions, it's literally a diamond for me, thank you

Please come back, your videos are great!

Just fuc**ng amazing video hats offf

but by what number do you change the weights like you never told us

this is video is super underrated. In fact the whole channel is underrated.

Wow, just saw this 😂, its excellent, thank you

Soothing voice to learn about transformers and warm room is perfect for recipe for my sleep.🛌

Wow .. what an explanation sir ❤ Thank you 🙏

Part 1 -- Cubic Curves ua-cam.com/video/YMl25iCCRew/v-deo.html Part 2 -- Catmull-Rom and Natural Cubic Splines ua-cam.com/video/DLsqkWV6Cag/v-deo.html Part 3 -- B-Splines and 2D ua-cam.com/video/JwN43QAlF50/v-deo.html

Part 1 -- Cubic Curves ua-cam.com/video/YMl25iCCRew/v-deo.html Part 2 -- Catmull-Rom and Natural Cubic Splines ua-cam.com/video/DLsqkWV6Cag/v-deo.html Part 3 -- B-Splines and 2D ua-cam.com/video/JwN43QAlF50/v-deo.html

Thank you very much for this very explanatory video. It is the first time we are studying this with my project students. We would like to make some comments about what we get from the explanations. Please correct us if we are wrong. For NCS, we use f''[x_{k+1}]=g''[x_{k+1}] condition in the middle points together with f''[x_{1}]==0 and g''[x_{n}]==0 at the end points. While, for CRS, we use f'[x_{k+1}]=g'[x_{k+1}]=(g[x_{k+2}]-f[x_{k}])/(x_{k+2}-x_{k}) together with some derivative constraints (such as f'[x_{1}]=0 and g'[x_{n}]=-1) at the end points.

That was dope

This video is amazing. You explained everything in such a simple manner. I am feeling really motivated to learn more about reinforcement learning and neural networks after watching this.

🔥🔥🔥 probably for the first time I'm using this emoji for education related things

agi: 1. ai develops understanding of win-loss conditions and sets policy params (inputs & actions) accordingly. 2. ai creates (= designs & builds) training env(s). 3. ai iterates, avals & adjusts policy parameters accordingly 4. done (or validation run(s) w/ human(s))

amazing video! thank you!

You are really gifted at this! Thank you so much!

This is so good I’m inspired to go back and learn Fourier and Taylor series

What if the spline is in 3D space and now there's a Z component as well? How do we account for that?

oh man, this tutorial is so well explained and compact, i already feel like i could come up with a rough code to do those subdivisions, tho the 3d part having multiple neighbors i haven't grasped yet, i think I'll look into that quad algorithm

Too frikin awesome

Explanation is really good😊

...man. I've been trying to learn this (and some other stuff when I gave up on this particular topic :')) for computer graphics exam for past 3 days and didn't get the intuitions for the affine operations at all. Until now. Wow. Thank you A LOT.

Great video!

Great video mate!

huhMAUjinus not homo-genius. but cool.

nice. but turn up your volume and use sound compression thanks.

My man you are great, I am implementing this in code as an exercise and I am understanding so much better!