I just woke up. I am very confused. Why am i here-

@4868985

Жыл бұрын

Same lol.

@JeredtheShy

6 ай бұрын

It’s an exclusive club we’re learning in our sleep

@olatundemarvelousanthony9231

6 ай бұрын

Like seriously same just happened 😂😂😂

@PJRand

6 ай бұрын

🌾👀🌾

@bmwsale8

6 ай бұрын

Same 😂

Just woke up, don’t know where I am or how I ended up here

@iamsan-san8094

Ай бұрын

same, last thing i remember was veritasium explaining game theory

@user-fr4pt2go8f

25 күн бұрын

Bro same i was watching fresh spawns i think...

@rahulkamath6916

25 күн бұрын

Ouch.. same here

@ghostdog1138

25 күн бұрын

Same, was watching serpentza.

@purpls.

25 күн бұрын

same😭

So, I just woke up to this video on my phone but the ironic part is I just learned about this yesterday.

@simonsong1743

Ай бұрын

Same as me and I kept the link in a file for learn it next time.

@user-vr3sc6hs5f

Ай бұрын

me too😂

@bennyrich7361

Ай бұрын

Oh and I didn't learn about this and have 0 interest in this...

@madscientist314

Ай бұрын

Same here

@demonzblood69

6 күн бұрын

Same. We are all connected.❤

Let me guess: you just woke up and this video was playing

@seanenright2759

24 күн бұрын

and it’s already an hour and thirty three mins in, how tf?!?!??

@perlecatt9123

24 күн бұрын

YESSS

@blacksky6016

23 күн бұрын

HOW DO YOU KNOW

@friendlyneighborhoodmemer18

21 күн бұрын

YES

@alkimozden

21 күн бұрын

woke up 44 minutes in

Watching this on my way to sleep for all the people who are waking up to this, it might break the cycle. 🙏💪

dunno why but this video was playing when i woke up in the middle of the night

Somehow this autoplayed on my phone while I was sleeping.

@0xSpaceCowboy

10 күн бұрын

Realy?

I came with an interest in neutral networks. I left feeling well rested.

i slept watching a different completely unrelated video and woke up on this what just happened

@nathanmckenzie904

Ай бұрын

Yup

@OmikronPsy

Ай бұрын

Same!

@rauld2572

27 күн бұрын

Singularity trying to nudge you in the right direction

@antiprohibit24

21 күн бұрын

You changed the weight without adjusting for the error. Happens all the time

@aqibrather6832

11 күн бұрын

this night same happned with me

I fell asleep watching a very simple maths video and woke up to this after dreaming that me and my friends were studying its contents. I’ve never done anything to do with this before but I understood it when I was dreaming about it so will probably give it another listen. It reminds me of being in College/University when SWIM was doing a bunch of drugs and accidentally designed a computer brain. Score for drugs 1,264,273,995,267,177, score for sobriety: still zero LOL

@therainbowtrout1820

26 күн бұрын

SWIM... There was an online forum I used to frequent. It's been years. I don't recall how to get there. I assume you know which I'm talking about. Does it still exist?

@bl8de3

23 күн бұрын

YAY drugs

@masturbates

22 күн бұрын

​@@therainbowtrout1820yes albeit not necessarily in the same regard

@orchdork775

9 күн бұрын

​@therainbowtrout1820 It could be Bluelight which is popular. There was another one I used many years ago, but I can't remember the name of it. I'm not sure it exists anymore.

From sleeping on a Geopolitics video to landing here, I am stunned😅

So to be the first, I’d just like to say my journey consisted of falling asleep to a video about why a magnet on the front of a car wouldn’t work, then it went to cursed units of measurement, then it went to professor Dave explains and then I ended up here, all in all I’ve been asleep for about 3 hours and I need more sleep… Anyone else wanna share the journey?

@pyromaniatic706

27 күн бұрын

I started by watching “why therapy sucks for men” I then fell asleep, and KZread showed me what gaming does to my head, to then finish here, it would’ve been Waaaay more if didn’t have my console on auto rest mode

Just woke to this playing. It was the catalyst to the craziest most vivid dream since childhood...im in my 30's.

Very surprised to see everyone woke up to this video as well. The algorithm strikes again!

I woke up and this was playing on the background

@MossawirAhmed

2 жыл бұрын

Seriously. Same here

@InnocentFieldHockey-sq8ws

Ай бұрын

@@MossawirAhmed

@user-go5vf3mu6f

Ай бұрын

Bruhhh same tf

@A-xm3kgBdedrtrtf5fufdjf9IJUOj7

Ай бұрын

🤣🤣🤣

what is this, i just woke up..

Assuming that everyone has had or currently has a learning capacity you realize that environment plays a huge part.

KZread is a good detector of sleep

@marius.y6360

2 жыл бұрын

Oh, so I wasn't the single one falling asleep watching something then ended up here being confused

@nononoah8

2 жыл бұрын

Amen

@tet9011

2 жыл бұрын

@@marius.y6360 me as well😂

@yahyaelfarh9624

2 жыл бұрын

@@marius.y6360 ⁹

@flick6569

2 жыл бұрын

Ur right

Apparently everyone waking up to this including myself 😂

@fatemehmohseni5414

21 күн бұрын

is this a joke or truth? what exactly happen?

@foxtrotcorporation

20 күн бұрын

​@@fatemehmohseni5414 load of people including myself suddenly wake up to this video. Autoplay at it's finest

@himanshurodiwal

17 күн бұрын

Yes I'm scared too

@ash_tray_6

Күн бұрын

It’s making me laugh so hard 😂

I’m pretty happy to be awaken by a such interesting lecture. Will watch it again

@JCel

12 күн бұрын

True! I woke up after it ended and the headline was interesting enough to hit replay while awake 😂

I watched this on purpose. :) Found it quite helpful! Cheers

If you're an audio guy, Squash functions are just compression by factor of Ratio (r). Threshold is the pickup weight input and knee is smoothing of weights between input and output over a certain range. And there you go. Compression in a nutshell. However the dB peak scale is non-linear. The dB scale is power of 2x10dB. That's what makes it the most confusing. So a ratio of 10 to keep it simpler is double the volume at the threshold gradually weighting less until the set peak where compression is zero. The knee rolls off that effect by a dB factor at a specified loudness and breadth of its impact. Seems gaussian to me. I don't know how the math works at the knee but it gives a smoother transition from boosted to left alone. So in a typical simple compression threshold at -24dB with 10 ratio would result in threshold at -12dB tapering to -10dB, -8dB, -6 and so on until you hit zero assuming your highest peaks are 0dB which is bad. Then you adjust the output to -8 or -14 depending on the sound and that scales the whole curve downward unaltered relatively by whatever output dB you set. If your threshold was boosted by compression to -12dB and you scale it down in output by -8dB then your threshold after processing will be -20dB tapering off up to -8dB in the same curve it had before the output was scaled down. That's why you have to adjust input vs threshold vs ratio vs knee vs output to get the best out of simple compression. Multiband compression is the same thing just much more complicated as it accounts for frequency where you can specify within a certain frequency range how much compression you'd like. Overlap them and yeah that gets quite complicated but it's super useful to getting the right sound especially in dialogue to grab and manipulate the loudness of tonality and sibilance while rejecting the background noise or any echo or unwanted reverb. The same principles apply in NNs in more of a deterministic and mathematical way. It entirely depends on the architecture and what it is used for as you are taking a larger dynamic range of inputs and compressing them to a smaller range of outputs. That's why CDs in the 90's Redbook audio was 16 bits wide. 2^16 made for 65536 levels of volume for any given sample. That was enough because it was replacing cassette tape which had horrible dynamic range. Now it's standard to have 24 bit audio which has a vastly higher dynamic range of 16,777,216 levels of volume at any given sample. For production and processing it's common to have 96 bit audio which has 7.92281625 x 10^28 levels of loudness. That's technically not better than analog but no human would ever be able to tell the difference. It helps computers and audio processing make very very accurate changes.

@wagyubeans1399

Ай бұрын

oh word !

@deang5622

Ай бұрын

Quite a pointless post really. Going to tremendous depth using an analogy to explain neural networks. Far better to understand the network rather than your analogy. And yes, I used to work in audio engineering. Analogies are useful as a means of explaining, of education, but your analogy is so specialised it has very little use in educating people.

Excellent explanation, excellent figures, and animations, awesome speaking! Looks like a dream course!

Everyone just waking up in this video

I suddenly opened my eyes and dreamed about this video while sleeping with my tai chi instructor at my beachfront property. Unreal.

Wow first time I’m actually glad I learned calculus in school. Nice to see it useful outside of the classroom.

@maximiliansgodzay3284

Жыл бұрын

T

@navinsonkar7195

Жыл бұрын

भघ

@zilog1

7 ай бұрын

Yep. Everyone thinks they know better. "I'll never use this!" Then why are they trying to teach it to you? 🙄

@Dutezy

Ай бұрын

just cus they tryna teach it doesnt mean its necessary or objectively useful. most schools dont teach how to do taxes, and those are mandatory @@zilog1 🙄

@XGX-OP

Ай бұрын

@@zilog1 Most people never use it again

Thanks 🙏 I finally have some understanding of why cnn’s work!

I knew an engineer brother of a friend who was working on how best to implement gradient descent into NNs years and years ago. I think he was one of the ones who gave up before CNNs became a widely used method. He certainly isn't a NN engineer anymore. He went on to predictive logistics which resembles RNN but really it was a much simpler feedback loop and balancing input versus output. Part of the Just in Time production to delivery process. Likely, the processing power and tech in the 90's wasn't powerful enough to realize the emergence big data is capable of now. Kinda wonder what he would have done had he been doing that 25 years later than he was. I know that he uses advanced NNs now of various types for his job but at this point he is an implementer rather than a developer. Tuning plays a big role.

I just woke up and this was playing. Now I better just know how to program a new LLM or I’ll be really upset.

Wonderful, elegant explanations! This is the way to present the basics of a hugely scalable system!

@dannyfrost2621

2 жыл бұрын

Right lol you and at and I yyyg

@HassanAhmed-rf9xr

2 жыл бұрын

@@dannyfrost2621 an me

@nishanmainali3359

2 жыл бұрын

@@HassanAhmed-rf9xrk,

@jeremytritle3980

9 ай бұрын

W😅 w😮😮 1:11 1:11 1:12 1:12 was

@jeremytritle3980

9 ай бұрын

@@HassanAhmed-rf9xra

Thank you for making this!

If you can us any shape coulad you use a Golden Torus mandala or hipnotic eye. I would try a this shape but it would Spiraled Like a slinky within a slinky?

What should be confusing is your vision or at least your conclusion! but the global context is great

KZread really just teach me Neutral Networks while I’m asleep.

Just woke up after it ended. I remember waking up for a few seconds thinking that it was interesting, hitting repeat and fell asleep after a few seconds again as it was still in the middle of the night. Now I'm wide awake and hit replay again to truely watch it haha 😂

Nicely explained. One thing near the start is that sigmoid only goes from 0 to 1 (It's tanh (x) that goes -1 to +1)

@seriouscoder1727

2 жыл бұрын

They r related ,, nice point to mention

Marvelous work! If this captivates you, there's a book with similar themes you’ll want to explore. "From Bytes to Consciousness: A Comprehensive Guide to Artificial Intelligence" by Stuart Mills

Brandon; great video! where can we find more visual representations of adding curves? @40:00 you begin to combine curves. how and where does one learn more?

@user-bb9lx9gu7c

2 жыл бұрын

Fourier series comes to mind. Basically, add a bunch of simple but different curves together to get one complicated but continuous curves.

@whannabi

Жыл бұрын

@@user-bb9lx9gu7c Fourier ne fout rien à la fourrière.

@michaelbacchiocchi8111

8 ай бұрын

@@whannabi😂

@7:40 at the last bottom-right neuron on the third layer; shouldn’t the connected weights be positive (white) to get the desired output of the horizontal pixels?

This is a lot of videos smashed into one. Honestly, excellent work.

@GuinessOriginal

Жыл бұрын

Where would he place GPT4 on his generality performance graph? Must be a step change

This is such a great tutorial! Thank you for making it. I will share the video with students interested in neural net and deep neural networks.

@tylerkendrick8271

7 ай бұрын

Uu

2:27:45 So your neural network has a neural network lol... I was thinking along similar lines right before you said this... "It could translate to the "rough doesn't fool a human" and then be "translated" again by a network that understands the specific language quirks better and has been trained on natural speech... But the straight intermediate (Latin? Lol) sounds better... I don't guess it even has to be a real existing language even, so long as it is set up to minimize "lost in translation" errors. You've got one of the clearer presentation methods for me... This stuff is really making sense now finally lol

I woke up to this like everyone else, apparently. I'm guessing the unusually long runtime increases the likelihood that someone would, as opposed to waking up on some random 20-minute video 🤷🏻

@purpls.

25 күн бұрын

we both woke up to this

@christianschroeder4

25 күн бұрын

​@@purpls.We all did

@MisterDemonYT

8 күн бұрын

Nah that can’t be, not every 3 hour video has everyone waking up to it

One of those videos you get hooked to when backed

This is great.learning neural networks while I drive to work. The internet is beautiful 😍.

does anybody know where I can find the result mentioned at 40:10 ?

3:33 How come the narrater's cough makes the result go from negative 0.075 to positive 0.075?

@ansowarrower5038

2 жыл бұрын

abs(0.075)

@duoko98

2 жыл бұрын

shutup

@ansowarrower5038

2 жыл бұрын

@@duoko98 Are you saying that because your mother has three? Get an education

@duoko98

2 жыл бұрын

@@ansowarrower5038 Lol cough joke just wasn't funny to me idk...

Simple and intuitive explanations. Thanks!

@wolfisraging

5 жыл бұрын

Exactly like yours.

@MachineLearningwithPhil

5 жыл бұрын

@@wolfisraging Thanks bud!

@MultiNemanja90

3 жыл бұрын

D@@MachineLearningwithPhil

@MultiNemanja90

3 жыл бұрын

r@@MachineLearningwithPhil ssss

@MultiNemanja90

3 жыл бұрын

r@@MachineLearningwithPhil ssss

@3.56, the activation function shown is tanh (-1 to 1) not a sigmoid/logistic (0 to 1).

@vishnuvasansrinivasan7797

2 жыл бұрын

but the activation function can be anything right!!! It can be anything related to what the input is all about like: ReLU, Sigmoid, tanh, etc...

@GermanischeTutorials

2 жыл бұрын

Essentially, the sigmoid function is equivalent to a tanh function just multiplied by some factor (as well as the argument)

I have a project where I'm taking some low resolution monochrome sprites and I'm attempting to reduce the shape of these sprites in a higher resolution. I tried to play with some scale filters to aid me in that process. It seems a lot like trying to make a vector font from an 8x8 character bitmap.

i clicked on this because i was curious just to discover that i watched the entire thing sometime when i was sleeping

I just woke up and turned my phone on to this??

That's strange, I just woke up exactly 7:30 am to this video playing. And I went to the comment section and turns out I wasn't the only one. I don't remember watching science related video neither.

This is super fascinating

For busy students: play at 1.25 or 1.5 speed

@vespenevapor1348

Ай бұрын

For busier students: ctrl + w

7:40. The bottom right neuron is supposed to be inverted. 2 black on top and 2 white on the bottom. The negative weights should actually be positive weights.

@nargesmokhtari9613

11 ай бұрын

Exactly

@nargesmokhtari9613

11 ай бұрын

Exactly

@_goldfish

10 ай бұрын

Exactly

@_goldfish

10 ай бұрын

Exactly

@michaelbacchiocchi8111

8 ай бұрын

Would the vectors need assigned values/weights in that case? Isn’t this just an example?

You explained just a one-layer back propagation. My question is: if I’m propagating from layer 3 to input and I’ve done layer 3, how do I know the expected value of neurons in layer 2? I need that to calculate the error right

So if they are saying the jet stream will straighten that intern will reduce the strength of low pressure systems. Also if the jet stream drops lower that will then make more areas cooler. P.s the golf stream is not the same as the conveyor belt

Watching this before the TensorFlow tutorial.....

Fantastic explanation 👌

Woke up to this and is exactly what i searched for yesterday, but couldn't find it

Why have so few actually chosen to watch this video, I woke up at 4am to it playing

Please make a video on computer networking and competitive programming

46:28 in b those have a corelation too

can you tell me if laptp with i5 12 h 16 gb ram intel iris xe good for neural network training.

Normally functions can’t have the same y value for different x values, does that apply here or no?

I just woke up.. went down watching vertasium

@BrianKenyon

Ай бұрын

Haha.. I’ve been falling to sleep to this video for a couple weeks now. Trying to get through it full consciousness. Heavy stuff.. haha

I fell asleep with my PC on When I woke up I saw this. Interesting. I did take differential calculus in college and programming for other reasons. Now I have an understanding of neural networks.

@TokyobuckettsLive

2 жыл бұрын

Yo!Same thing happened to me,awesome

@HassanAhmed-rf9xr

2 жыл бұрын

@@TokyobuckettsLive yes not similar but i was charging my portable charger a left the vids on so it could charge. Came back later an saw this thought it was interesting an now im here hehe.

@LG-qz8om

7 ай бұрын

Is that what you call "deep learning"? ;-)

At 9:30 please agree that that last weight from the black solid to the output ”solid” should’ve been _black_ (because minus x minus = plus) and not white. Or I will have understood nothing

What happens if you ask a neural network that the plural of BIAS is? Does it say BIASEEEZ ?

Thanks!

41:48 imagine it in n-dimension It can do amazing stuff in a matter of second. Can you explain neural net in time series please These lessons touch my heart and for the first time i can imagine abit what is going on in that black box

Woke up 2 hours 44 minutes in , i am CONFUSHON

My auto play was turned off when I went to sleep and yet, somehow, I woke up to this playing. Not sure if I turned it on in my sleep or something but then again it seems I’m not alone in the endeavor

0:40 if you tried making a rule you wouldn't be able to do it. Why? Isn't the rule pretty clear? If only the 2 top or 2 bot are black, it's horizontal. If only the 2 left or 2 right are black, it's vertical. Every other composition where 2 are black is diagonal. If 3 are black, it's L. This just seems programmable. What am I missing?

@seriouscoder1727

2 жыл бұрын

It may be programable but what if you rotate it Or you want to find cat , not cat program

@JoaoPedro-dx6pn

2 жыл бұрын

@@seriouscoder1727 Exactly. He used this example because it was more simple to explain :)

@radovankrizalkovic9084

2 жыл бұрын

@@JoaoPedro-dx6pn I see, so of course if it was a more complicated object in an environment, it would be really difficult to describe all rules for it. Is that what he meant?

@JoaoPedro-dx6pn

2 жыл бұрын

@@radovankrizalkovic9084 Yes. Specially if you dont know all the possible states. These algorithms are applied to filter/classify tons of data, and it will handle tons of different states that we cannot predict.

1:20:40 Since this course is about learning algorithms this is important to classification. Vector: noun Mathematics. 1: a quantity possessing both magnitude and direction, represented by an arrow the direction of which indicates the direction of the quantity and the length of which is proportional to the magnitude. 2: such a quantity with the additional requirement that such quantities obey the parallelogram law of addition. 3: such a quantity with the additional requirement that such quantities are to transform in a particular way under changes of the coordinate system. Biology. 1: an insect or other organism that transmits a pathogenic fungus, virus, bacterium, etc. 2: any agent that acts as a carrier or transporter, as a virus or plasmid that conveys a genetically engineered DNA segment into a host cell. Computers. 1: an array of data ordered such that individual items can be located with a single index or subscript. verb (used with object) Aeronautics. 1: to guide (an aircraft) in flight by issuing appropriate headings. Aerospace. 1: to change the direction of (the thrust of a jet or rocket engine) in order to steer the craft. ... I am tempted to say Physics would include a unit Physics 1: a quantity possessing magnitude, direction and unit.

@joshsamuel7868

2 жыл бұрын

I🏵️🌪️🏜️🌿🤹🧚🦹🧚🧚🧜🙍🛌🙍🏜️😚🏜️🌿🏜️🛌🤼🙍🏄🤦🏇😈🛌🙍🤦🙍🚣🏄🤦🤦🤦🏄🙍🙍🤦🌪️🌿🌻🍃🍃🐯🦕🐯🏇🏇🤺🤺🏋️🤵😉🤭

@Gpeto91

2 жыл бұрын

77 por

@unspecialist

Жыл бұрын

Thanks but most of us finished high school too 😅

@wide4583

5 ай бұрын

Oo😊

so glad im not the only one who woke up to this vid in the middle of the night lol

I woke up and this was on my phone lol

Guys how about a Tensorflow tutorial in depth! Please?!!

@1ycx

5 жыл бұрын

Check out the "TensorFlow Basics to Mastery" Coursera Course - www.deeplearning.ai/tensorflow-from-basics-to-mastery/ I am currently doing Course 1. Doing courses separately is free. The specialization is paid.

@shwetagoyal9801

4 жыл бұрын

@@1ycx I think you misunderstood something. You have to pay for a certificate. You can do courses separately but these courses come under specialization only. You get certificate after every course but you have to pay for that. If you don't want certificate then only these courses are free.

@ben34256

4 жыл бұрын

Check recent uploads

@user-cj3yu9nv1u

4 жыл бұрын

@@shwetagoyal9801 I think that Koga Master is talking about the fact that you are able to learn TensorFlow on Coursera for free rather than getting a certificate for it.

@asepnurochman3869

2 жыл бұрын

@@1ycx ini 0 88

I'm only a minute or two in but this is amazing... I'm understanding it so well that I'm considering learning to code

@vinobrien5738

2 жыл бұрын

⁰4

@ahmad.alotaibi

7 ай бұрын

@@vinobrien5738t😅aaà

the graphs from 40:00 foward makes no sense to me, how can you have 2 values and not make a straight line? you have y output and x input and you get waves? that graphic makes no sense on what you are talking about... unless if you have a diferent value called repetition or time, but still the first ones without the multiple nodes will also make waves since you are adjusting the values right? I dont understand it...

@kiiikoooPT

2 жыл бұрын

are you combining the results from the 3 layers in the same graph? isn't that the same as making 3 iterations on the 1 layer mode?

@seriouscoder1727

2 жыл бұрын

Logestic is kind of liner classification

I am also here on complete purpose. And can’t stop watching.

First 30s wrong example but good video in general. Yes, you can simply detect what pixels are dark, what are lighter, there is function for that. Also 4 pixels is bad example because you could create like 8 if statements define tolerance (same tolerance as in Photoshop which is distance between colors) and it would outperform every model.

Fantastic, thank you.

Wishing you goodluck keep it up 🙏

May be my english not good and i did not understand correctly. So can anyone help me explain why at 1:09:51 error of O is not -0.51, i mean 0 - 0.51 = -0,51. Thank advance

@seriouscoder1727

2 жыл бұрын

Maybe the multiplied isnt it?

Seems like neural net teaching comes in two forms - math or python libraries. It'd be cool to see an intermediate form - some code that implements the math but isn't a library.

@seriouscoder1727

2 жыл бұрын

kzread.info/dash/bejne/k52mxaOrpdnUe84.html And one more from dayako

@kristoffersvartbkkengrinda4029

2 жыл бұрын

@@seriouscoder1727 Super good video. 3blue1brown is really good at everything mathematics. And a good teacher.

@trevortrevose9124

Жыл бұрын

Ong so true not everyone likes python

@allenklingsporn6993

8 ай бұрын

All of the libraries mentioned are open source, meaning that you can go read the source code. Honestly, though, understanding the content is going to be much more difficult with the source code because it would take away several levels of abstraction that are implementing highly technical details. Doing this, for example, with Pandas or numpy (or worse, with straight python) would take quite a long time and be useful to almost no one, negating the investment into a video.

@allenklingsporn6993

8 ай бұрын

​@@trevortrevose9124Packages are also available in R, C#, and several other languages, friend. Python is for sure the easiest and most popular general purpose programming language to use, though.

Amazing video, thanks!

This was on with no way to stop it for several minutes. I think Murphy was trolling me today

3 am be hitting when thes videos show up on my feed

I also just woke up to this video playing already for an hour after fell asleep when watching a video about wave function of particles, how strange

1 am and he finally hits me with the human level intelligence section

Hello here, I've a request with you, please make small video of about 6mins by breaking into several parts--creating a playlist, so that viewer can pay their interest.

@seriouscoder1727

2 жыл бұрын

Watch krish clips or sentex

So in slept with the video 1 trillion lions vs the sun and now I woke up 1:38:12 into this video

Very clear.....thank you

What are the pre-requisites for watching videos on Machine learning?

@yumbemelvin2981

3 жыл бұрын

a brain

@shivamsoliya6529

2 жыл бұрын

@@yumbemelvin2981 🤣🤣🤣

@seriouscoder1727

2 жыл бұрын

Abit linear algebra(matrix) abit statistic high schol in enough

@Soulfulreader786

2 жыл бұрын

Yt and internet 3g

This already looks like an interesting course , thanks FCC !!

@grahamconquer8117

Жыл бұрын

Yes something to help me with my deep learning course thanks 🙏

Just woke up. Saw this in my recommended section and immediately clicked, because I didn't understand the datascience introductory course I had.

Can anyone explain please - why in @7:40, the last(3rd) layer and the last neuron(4th) is horizontal in the bottom, shouldn’t it be horizontal on the top because of black synapses? Thank you!

@vincentmeessen6659

2 жыл бұрын

You are right it should be horizontal on the top of the square for the 4th layer. He just made a error when creating the PowerPoint ;)

A simple rule definitely could solve the first problem. I'm not sure that's a very compelling argument to use a neural network in that case.

@fudgeracoon2529

2 жыл бұрын

shut up man

@xoloser3

2 жыл бұрын

@@G83X Hey, in retrospect I see that he's just using a super simple example as a point to teach. Which is totally fair.