Sir we loved your videos, in our college , we are getting taught Deep Learning through Amay Gawd, he send us your videos as reference material. you are a blessing to this world.
Hello Krish you did great job...Really really appreciated. I regret why i didnt find it before. You make many important videos/ content/ topics. Ok But could you plz upload videos of CNN ( Inception, Resnet, 1×1Network)..
Sir thank you so much, really amazing video with such amazing explaination. Just one thing at 13:30 , after erasing the formula, we you recalled it, you just missplaced the position of signs. the overall complete video is so much informative. Thank you so much
He made a mistake, it is not a multiplication, so, The result of 6*6*256 is connected to a dense layer of 4096. So, each neuron of 9216 is connected to each neuron of 4096 hope it will help
this is the number of filters that are used, the image size is 227x227x3, the the filter size is 11x11x3, the last nuber , here is 3, has to be the same with the depth of the input 227x227x3 , here it is 3 (RGB), Now, the 96 came from , 11x11x3x96 hope it will help
You say "now I'll explain normalization" and then say "so normalization is applied to this particular thing pixel by pixel". Whaaaat???? What is Standardization?
![The moment we stopped understanding AI [AlexNet]](http://i.ytimg.com/vi/UZDiGooFs54/mqdefault.jpg)
Sir we loved your videos, in our college , we are getting taught Deep Learning through Amay Gawd, he send us your videos as reference material. you are a blessing to this world.
Yeah So here it is coming🤩🤩, please cover all the architectures and thankyou.
@Krish sir, you're a big help in examinations... thanks for all your efforts..
Please tell us pros and cons architecture to architecture. It will help us too. Thank you 😊 great explanation with presentation
True Rockstar of Data Science, this was brilliant
Hello Krish
you did great job...Really really appreciated. I regret why i didnt find it before.
You make many important videos/ content/ topics. Ok
But could you plz upload videos of CNN ( Inception, Resnet, 1×1Network)..
In the second convolution layer, why were 256 images created in the output? Shouldn't 96x256 images have been created?
Bhaiya you are a gem !
Sir thank you so much, really amazing video with such amazing explaination. Just one thing
at 13:30 , after erasing the formula, we you recalled it, you just missplaced the position of signs.
the overall complete video is so much informative.
Thank you so much
Thank you sir... Explain about resnet and google net sir
Thanku sir ur videos amazing
Nice .sir make videos on image classification using mobilenNet architecture in python
Good explanation. Sir, Can you please teach how to change SoftMax to Euclidean loss function for prediction. Thank You
Thanks buddy
thank you sir
sir I want explanation about faster R-CNN architecture along with code sir
thank yoou
Please explain Inception v3 in upcoming videos.
U-net Architecture also Please
hello sir, please make video on VQA
Hi Thanks for your video. How we get 4096 ? (Fully Connected Dense is 6*6*256 = 9216)
He made a mistake,
it is not a multiplication,
so, The result of 6*6*256 is connected to a dense layer of 4096.
So, each neuron of 9216 is connected to each neuron of 4096
hope it will help
@@deepknowledge2505 thank you
Sir in your GitHub code you have taken valid padding in every layer but in some layer there is same padding 🤔
can two classes have same name while training deep learning model(i deliberatly need it)?If yes, what are its effects?
It's better to create a single class containing data-points from both classes.
Will this be implemented using PyTorch or Keras/TF ??
I hope its Pytorch 😂
Keras
Sir! Can I know how we consider no. Of Kernels as 96 ??
Is this a transfer learning Alextnet model or From scratch ??
When is BERT session?
Waiting
Isn't the initial size 224x224x 3 instead of 227x227x3?
Bro you are cheetah 🔥🔥
how do ypu calculate kernal size as 96
sir how you got the value of kernal as 96
this is the number of filters that are used,
the image size is 227x227x3,
the the filter size is 11x11x3, the last nuber , here is 3, has to be the same with the depth of the input 227x227x3 , here it is 3 (RGB),
Now, the 96 came from , 11x11x3x96
hope it will help
@@deepknowledge2505 hi, i have the same problem as Vijueligar, but i can't understand your explanation, would u please explain a bit more? Thank u
Anyone knows how can we design the architecture of network in details like in the video?
Sir, RCNNs plssssss🙏🙏🙏
6:31 227-11 not + sir
You say "now I'll explain normalization" and then say "so normalization is applied to this particular thing pixel by pixel". Whaaaat???? What is Standardization?
Hi bro How to use deep learning..training..
Models??
sir please provide code MATLAB software
do we need to remember the filter size, stride rtate and no. of kernels being applied at each layer
(227-11)/4=54+1=55 🤔