Brilliant , You hit the nail Brandon . Excellent vd , excellent style of teaching which is to have a general visiual broad perspective of an abstract idea

All of these Bayes explanations are so abstract and constructed and unintuitive...

Frankly speaking, it seems you are just reading the things and flipping the slides. It doesn't feel like u r teaching. Moreover, you don't explain the concept, you just say it out without any explanation. Sorry tk say but very bad teaching. you might Have knowledge but teaching is not good

This is the first video of yours I have watched. It was so good that I subscribed to your channel. BYW, your voice is a lot like Brian Greene. This is good because it is a good lecture and documentary voice.

The best explanation I've ever seen

Great video, many thanks! Can someone explain the part between 19:30 to 21:40? All the calculations and finding the final posterior distribution

Thompson Timothy Clark Carol Williams Brian

19092024

Excellent example for back prop and chain rule!

Really helped me contextualise the matrix procedure in practical sense. Thank you!

This is the clearest explanation of convolution that I've ever come across.

7:00 autocorr

This video was shot before the contemporary LGBTQ movement.. it made it so easy to explain certain facts..

Beautifully explained!

Master piece! One question: Is convolution the same or a kind of filtering?

Awesome description of what neural networks are!

This is the BEST video explanation EVER! Animation, simplicity, voice, oh god, you deserve an award in the machine learning world!

great video

Thanks!

I like it! Thank you!

Good presentation

17:57 One query here. How is the P(m | w=17) distribution function calculated? What is the spread (S.D.)? How do we, for example, arrive at any certain value of the probability of getting m = 15.6lb given the true weight is 17lb? Thanks! Nice explanation.

For anyone confused at 7:40: The weight line connecting the last neuron on the second layer (white top right pixel over black bottom right pixel) to the last neuron on the third layer (2 white pixels over 2 black pixels) should be white not black. On the slides, the weight line is white. It's just a small mistake

"Cute" is a word used by a HIGH proportion of females, and nearly not at all by males. We should choose a sample containing 50% female, 50% male to estimatethe ratio of "cute" meaning, in actuality, ugly. Now, about 90 to near 100% of females use cute to refer to ugly objects and prganisms. Organisms to which females are highly unlikely to regard as "cute" tend to be hairless organisms, such as slugs, biting indects, slime molds, though some significant percentage of females DO refer to baldo males, hairless cats, and babies as cute. These miscategorizations, such as males who shave their heads for the ALWAYS twin purpose of pretending to be socially dominant, AND to hide their follicle shutdown, may skew our data, and so such persons must be eliminated from data sets. "Cute" of course, involves Other female miscategorizations. As science has proven that females use the term in reference to sharpei dogs, we KNOW that cute does NOT mean sexually appealing, but instead refers to massive wrinkling. Yet, females themselves go to toxic lengths yet fail to remove wrinkles from their own skin, even though many species of felids and canids require loose skin in order to transport pups and kits. Applying this latter developmental period phenomenon , we CAN use some Bayesian inference to estimate that females may very likely be using the otherwise indefinable word to mean that she desires to carry any hairy, wrinkly organism in her teeth. Thus, we approach the true, previously unknown meaning of "cute, " formerly unknown and indefinable. Ne can anly speculate the meaning of the word to the male narrator here., as the sample size, one, is too small to interpret any meaning whatsoever. Is the male seeking to "female-speak, imitating the noise uttered by that species, in hopes of attracting a sample, however variable in number, for reproductive, or other, pruposes? Does he mock the indigenous female who uses the word to identify the ugly? Is this good? Is it bad? Or is it Clint Eastwood? Rare events for which mean, median, mode, cannot be established, remain difficult to estimate probabilities. On the one hand, females use the word ubiquitously, as often as that species can fit it into their communication signaling. Thus it MAY be essentially meaningless, and observers might be misconstruing a noise uttered from infantile developmental stages ATTEMPTING but FAILING to form an actualword. " Cute" may, thus, be a TOTAL misinterpretation of vocalizations, just as the Ancient Greeks, hearing languages foreign to them, heard only "bar-bar-bar" in sophisticated unknown languages, called them barbar-ians. Is it, finally, that we are hearing a tongue to which we have no Rosetta, so far hidden from us, and females speak profound insights, complex prose, poetries to which we remain oblivious, our ears buried in sharpei skinfolds? Or, is it that they merely babble imitatively at one another, "cute-cute-cute", without meaning, as they plot to cast offal upon us more earthbound creatures below? In any case, that single most common female utterance so far escapes us completely. All we can hypothesize, is that, used in nearly every female signal, it is either of VAST import, or as meaningless as the apostrophes littered about in youtube commentary by the fabled monkeys on typewriters, someday, should the Universe persist sufficiently, to become part of profound, Shakespearean works of literature, to be discovered by more intelligent species than ours. Those canids will howl their unearthing of meaning, and caw in their Raven voices, in ecstasy, at last, understanding the combination folded hirsute pelage apparently so attractive to the females of a long-disappeared naked ape.

Excellent . Thank you soooooooooooooooooooooooooooooooooooooooo much !😊😊😊

Thank you

Awesome! I just didn't expect you to actually talk about backpropagation and linear layers but I'm not complaining.

Lets assume that i have an image of a number that means that i need to pass it from horizontal vertical and diagonal kernels to get the features?? I want to make a convolution library from scratch

This really make me understand CNN more intuitively, lucky to meet with your vedio😄

Hollllyyyyy cow. Thank you. I have only just started this vid but as a TBI survivor who taught myself how to converse due to recall and memory issues along with researching the SCIENCE…. Can’t tell you how invaluable this validation is.

this video talks about two examples; 1. theater 2. a dog with name of Reign. The first part is easy to follow, but the dog's weight distribution is not easy to follow.

The interaction with the audience feels so personal.

amazing video

wow🙂

Probably, one of the best intuitive explainers of why we like to use gradient descent in neural networks, which I ever seen.

Wow! One of the clearest explanations of Bayes Theorem I’ve come across!

this was super helpful

excellent the AI chip can not avoid the principles of the system architecture of the hardware fundaments the rules and algorithm like round robin algorithm, FIFO etc and neurons also as follows the signal process of the data communications as well. here keep in mind binary , qubit and hybrid process. the voting process of blockchain for digital encryption is kind of like similar. Chip has main 3 gates AND Logic Boolean , OR Logic Boolean and Not logic and total combo of 7 gates.Qbit49 is a quantum are Shor's algorithm probability has 3 state also 3 methods quantum tunnelling, entanglement, superposition , binary has yes /no ,Qbit has Yes, No, (yes or no).

❤❤❤❤❤❤

Best Knowledge for real. The video is very helpful. ❤

Great presentation, Brandon. I prefer your simple graphics and pace over the highly distracting, animated videos from other educators.

You will spent hours trying to find the right video, this 26 min clip is all you need.

Great explanation!!

Thanks for such an amaizing video

Very good

thanks

The first one put down is in the wrong spot.

Now in 2024, and I can’t imagine the degree of triggering all these assumption examples would give a certain disturbed minority of the population… Also I guess it’s only because statistics inhabits the furthest recesses of YT land that someone hasn’t called for it’s banning or demonetisation at the very least!

Hi Brandon, when giving it an unseen image, how do you know whether to draw a line from the vote percentage to the x or to the o?

You are not suppose to copy code from vid