At 2:28 min. the picture might be misleading as an activation function normally comes right after the convolution, so it's convolution - activation function - pooling.
This is not for everyone, u first need to understand basic machine learning knowledge and enough math knowledge, and then basic understanding of neural networks, then these will start to make sense
4:15 "One of the best popular ways of doing this is using autoencoders. This allows you to 'squeeze data' in a space with low dimensions." Like, what does that even mean? I feel like most of this video was throwing technical jargon at you with no context. Kinda bad imo.
Classical neural network proves inefficient for computer vision. Why? because if u take a large input(large number of pixels, and if it's colored then 3 color channel as well) then we'll need a huge number of connection(neurons) and parameters. Using CNN we use filters and pooling techniques downsample the image to extract only essential features. It makes it more faster and efficient. That's what I think.
@@Pradunya thanks!! But is it not so much application specific answer... What if we have different data set than image ? My question is why we use convolution only not anything else in general???
@@krishnamishra8598 I think there are different models of neural networks as well which are used according to the need. Even CNN is not the best for images( eg there's RCNN better than it). So for other applications we'll use them accordingly.
The music disturbs the explanation! I wish to hear the explanation without the interference with music!
@Arpit Kaushal what is this?? I did not understood
True
This guy sounds the same as one from the channel Bright Side
prretty sure it's a robot voice, like google translates voice
Ai generated
At 2:28 min. the picture might be misleading as an activation function normally comes right after the convolution, so it's convolution - activation function - pooling.
MaxPool(Relu(x)) = Relu(MaxPool(x))
@@hamzaaitbourhimhmmm good information
This is not for everyone, u first need to understand basic machine learning knowledge and enough math knowledge, and then basic understanding of neural networks, then these will start to make sense
What if you have Artificial Intelligence and Data Science - II exam tomorrow and you know nothing about basic machine learning
@@pravinnichal8147 hi bro which branch which subject do you pass
I
But I was here to study for my semester exams
Hey guy from Bright Side, Thank you
If I visualize this point at 1:31, then I understand CNN.
What a great intro.... 5yrs later
4:15 "One of the best popular ways of doing this is using autoencoders. This allows you to 'squeeze data' in a space with low dimensions." Like, what does that even mean? I feel like most of this video was throwing technical jargon at you with no context. Kinda bad imo.
why do we use convolution ??? why not just simple ANN in case of image ?? main question is what is need of convolution in CNN?? please Answer....
Classical neural network proves inefficient for computer vision. Why? because if u take a large input(large number of pixels, and if it's colored then 3 color channel as well) then we'll need a huge number of connection(neurons) and parameters. Using CNN we use filters and pooling techniques downsample the image to extract only essential features. It makes it more faster and efficient. That's what I think.
@@Pradunya thanks!! But is it not so much application specific answer... What if we have different data set than image ? My question is why we use convolution only not anything else in general???
@@krishnamishra8598 I think there are different models of neural networks as well which are used according to the need. Even CNN is not the best for images( eg there's RCNN better than it). So for other applications we'll use them accordingly.
remove the music background please.... super annoying
This video is very useful to me...thanks
Why does the voice sounds like the one from bright side videos
1:36 i still dont quite understand, why its depicted as stacked of boxes and theres boxes inside pointed to next stacked of boxes?
Perfect ! thanks
many thanks!!!
Can you help me haw to detect electricity theft attackers based on cnn_lstm
Thank you
Is CNN a machine learning model?
At 2:57 how did you get that 3 answer
Great video!
which machine part does CNN train for example in a car?
thanks alot
thank u 🙂
very helpful
Love it!
great work!
Playlist?
Thanks alot
👍👍👍
Awesome video 👍👍👍
contact to reach out for help?
Awesome
nice
Excellent 👌
didn't understand a thing.
greeaaaaatttt
9/9
Background “music” sucks. Thank you though.
hjj