VGGNET Architecture In-depth Discussion Along With Code -Deep Learning Advanced CNN
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- Опубліковано 12 вер 2024
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You just have an amazing teaching style, Krish!!
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Hello Krish ! I want to ask that is DSA(LinkedList, Heap, BinaryTrees, BST, Graphs, Priority Queues), dynamic programming and competitive programming round is there when hiring for a data scientist fresher in offcampus or just having a good grasp on data science and AI is more than enough because it's very difficult to master data science and competitive programming at the same time
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this is a great explanation for Vgg, thank you for simplifying it to the world.
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You know things have changed when he said "welcome to my vlogging channel" instead of "welcome to my youtube channel"
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224x224x3 - > 3 means 3 input channels? Is that what you are saying.?
Great video! Thank you for explaining the details!
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hii sir, can we give 30x30 binary image as an input to alexnet or VGGNet?
Thank you sir very much, you made my life easy
hey Krish.. why does the dimension after using 3*3 filter remain same? like after using filter for the first time we should be getting output of 222*222 right?
'same' padding means... you will apply zero padding... hence you will get an image of 226X226 after pading
@@zindaginamilegidobara3372 putting all the values in formula [(n-f+2p)/s + 1] keeping the p=0 and s=1, will give (224-3)+1=222 !! Output pixel dimension is supposed to be (222x222x64). I am confused why Krish has used kernel size for conv layer as 2, while doing the calculations at 7:28
@@animeshsharma7332 the calculation is for the output of pooling layer so the value of s will be 2 not 1.
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Thank you !! Krish sir
Excellent teaching
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Amazing explanation!
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Sir can you say how 4096 kernel size is come......
we use flatten in which it will convert into that 1X1 and to do so, we have a pixel with eight surrounded pixels (top-left, top-center, top-right, left, right, bottom-left, bottom-center, bottom-right). multiply the number of pixels you got that are 512 with 8
512*8=4096
after the execution how do we normalize the training and validation curves (overfitting problem)
apply dropout... before training
Great Sir Can you do Xception Architecture In-depth Discussion ? If you make a video about it that would be great. Looking forward to it ❤
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can two classes have same name while training deep learning model(i deliberatly need it)?If yes, what are its effects?
why i have got error message ("The kernel appears to have died. It will restart automatically"). Please suggest on it.
Please make a video on VGG+ Capsnet Implementation on customized data. Capsule Network Implementation on data other than MNIST.
Thankyou.
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where can i download the crop dataset from sir ? can you share the link for the crop dataset
yesss you are the number oneeeeee sirrr :*
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Brother... comparison should be in terms of time complexity, space complexity and performance... and their tradeoff points....... not just filter sizes, strides, or pading... that is not the point of interest for the interviewer.
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can any one tell me if 224*224 image is passed to 3*3 filter then how 224*224*64 .why 224 is not changed in first 2 convolution layer?
Same doubt? Are you get a answer?
@@karthickraja1026 yes padding same is used
@@aibasics7206 Yeah got it!
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this video provides wrong information please ua-cam.com/video/PGhbpnfC3Qc/v-deo.html it covers bgg 196 and says that it is bgg 19
Thanks a lot, you're a wonderful tutor, pleas may I know your reason for keeping padding as same. Does
it mean padding does not have a value assigned to it. Thankd
nice explanation
Please make a video on Residual Network, Inception Network and CNN on RGB Images
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Can we write the code to see the weights assigned to the layers...???
Awesome sir!!!😁😁
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I just want to know vgg19 model and its code implementation so that i could explain this in my project viva.can someone suggest me what videos from this playlist or any other playlist i could refer in less time to be able to explain this . I do not have the time to go through all videos from starting. deadline is near. can someone help?
Hello sir, as in vgg-16 there are 13 convolution layers and 3 FC layers and 5 pooling layers. What about VGG-19? How many convolution, pooling and FC layers. Thanks sir
VGG 19 will have 19 layers in total (16 conv , 3 FC layers).
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This is one of the best videos!
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Extraordinary!! Answered many questions for me. Thank you!!!!
thanks buddy
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great tut!!!
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how can i add more layers?
Please tell that can I use the same vgg16 from keras for time-series data for activity classification?
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Hello Krish,
Can we use vgg19 for regression problem?
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didi ji 19 is not provided here it is 16 there fraud do fraud by saying that it is 19
can we applied on csv file
Can u please make video on covid ct scan image classification
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You are saying u use vgg because u can remember it easily ??
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vgg16 can be apply text data
Nice Explanation ... Is it possible to VGG net alg for structured data I.e. CSP data set
Sir what happens when we change input size of the image let say 2048*2048
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7×7×512 = 25088. So, did not get how fattening is occurring and getting 1*1*4096.
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great work, sir I need urs notes of the whole you are teaching in videos, and codes as well of cotton diseases, one question is that why vg16 is useful can we use it on raw data as well
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I am unable to find the link to download dataset. Could someone provide the link for dataset?
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Sir I am not able to join your Telegram Channel
this video provides wrong information this video doesn't even provide the full form of Vgg please ua-cam.com/video/PGhbpnfC3Qc/v-deo.html it covers bgg 196 and says that it is bgg 19
How to find the performance metrics after this part?
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didn't you have overfitting?
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OH ho Bhaiya full Graphics card flaunt !!.
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Can anyone tell whats the fullform of VGG???
Visual Geometry Group from Oxford
@@NidhiSingh-bw7sb Thanks Nidhi🤩
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Hi krish
this video provides wrong information this video doesn't even provide the full form of Vgg please ua-cam.com/video/PGhbpnfC3Qc/v-deo.html it covers bgg 196 and says that it is bgg 19
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