CNN architecture | Explaining the Architecture of CNN

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In this video, we will understand the complete CNN Architecture. A CNN architecture represents the design of the CNN. CNN architecture consists of Convolutional Layers, Pooling Layers, and fully connected layers.

In previous videos of this playlist, we have already covered the details behind the convolutional operation, pooling operation, and fully connected layers. Now its time to put all those tiny pieces together and construct an entire CNN architecture.

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Timestamp:
0:00 Intro
0:56 Convolutional Layer
2:30 CNN Architecture
8:45 CNN vs ANN
9:47 Implementation Challenges
11:58 End

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Follow my entire playlist on Convolutional Neural Network (CNN) :

At the end of some videos, you will also find quizzes 📑 that can help you to understand the concept and retain your learning.

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You are amazing man, there is something unique in your explaining style, you are so gifted ..

wasm
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Your greatness is truly commendable. I extend my heartfelt gratitude for the invaluable information you provided.

dalao
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LORD OF TEACHING LORD OF ML I HAVE NEVER BEEN IN CURIOSITY TO LEARN THESE TOPICS BUT YOU💥💥💥💥

Kk
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I'm so happy to finally understand this topic! Your videos helped me a lot, you're great :)

nicolem.silvestre
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I'm So gifted to have your videos !!!! 100% concept Understood

Gojo_sataro
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At around 4:32, you are saying that that the filter for 2nd Convolution must have same 4 channels as the output after the 1st layer. Should it not be 3 as the coloured image is an RGB, so filter for the 2nd convolution should be "(3x3 x3)x8", 3x3 is the filter size, followed by the no of channel and finally the no of filters applied in 2nd Conv, ie, 8?

NavnilDas-on
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Amazing channel, amazing syllabus.
You are going to grow up in a short term.Please upload more videos

furkantektas
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The Playlist is really useful bro Thankyou so much👍👍👍

kavyasreekavya
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Best content. Thank you. Please upload more like this.

dmlane_sougata
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amazing videos brother thank you so much much love ❤

dxlorean
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A small correction at 6:18. I think the dimension of FCL should be 120*288.

dmg-s
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It was very useful video to understand CNN. Thank you.

aysegulsezen
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simple is the best ! Great teacher <3

blackyogurt
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this is gonna save my ass in my midterm exam on saturday!

arhmn
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Excellent Work Bro! Can you also share the pdf version of slides that you have used

learnhome
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Thanks for very clear explanation. I wnat to know for complicated data like music data where we use mel spectograms and the number of feature are diffreent for every song, if we do not apply segmentation then we have to deal with diffrent number of input features lets say, (1456, 80) where 1456 are the number of frames and 80 are bins then next song (3789, 80), then next (7867, 80), .... so how to specify parameters for the cnn for this because input is change every time ? and how many layers for such data will be reasonable ?

aneekaazmat
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why you select 120 neuron specially in the FC3, i can not understand

mohamednour
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Brother, I want to learn much more about CNN. Which book do you recommend to read?

en.inigo.
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@coding lane - Can u pls share the PDFs for all the videos in this playlist. Even you u charge fee it is fine. Please share it.

adarshvadapalli
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6:16 no one was talking about it comment section so I had to

kashyap
welcome to shbcf.ru