CNN architecture | Explaining the Architecture of CNN

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) :
📕 CNN Playlist: • What is CNN in deep le...
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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📕 Which Cost Function to use? : • Cost Function in Neura...
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✔ Complete Neural Network Playlist: • How Neural Networks wo...
✔ Complete Logistic Regression Playlist: • Logistic Regression Ma...
✔ Complete Linear Regression Playlist: • What is Linear Regress...
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[@wasm79]

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

[@CodingLane]

Haha… Thank You so much! Means a lot to me

[@dalao3]

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

[@aysegulsezen4280]

It was very useful video to understand CNN. Thank you.

[@ayorayyan2794]

Thank you for valuable lesson

[@hassanahmedkhan3834]

very good series!

[@kavyasreekavya2213]

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

[@CodingLane]

Glad to help!

[@furkantektas8271]

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

[@CodingLane]

Thank you so much!

[@rajnigoyal4577]

amazing session 👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍🤏

[@dmg8529]

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

[@Kk96503]

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

[@CodingLane]

Haha… thanks a lot! A great comment from you!

[@blackyogurt]

simple is the best ! Great teacher

[@CodingLane]

Thank you 😇

[@user-uq9cv3xe3v]

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?

[@creepsow1236]

very nice aaa frr

[@TheSougata1]

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

[@CodingLane]

Thank you very much! I will keep uploading more videos! Hope you find my other playlists useful as well.

[@TheSougata1]

@@CodingLane Yes. I have watched Neural network and CNN playlist

[@aneekaazmat6653]

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 ?

[@a.r4hm4n]

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

[@learnhome9659]

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

[@CodingLane]

Hi... sorry for sharing it so late. Here is the slides for this video. drive.google.com/file/d/1tEcvunzhLpSkjlcRiQA5sIOtbGZwTtJ2/view?usp=sharing

[@engr.inigoe.silvagalvan1161]

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

[@bennybenbenw]

Add relu between conv and pooling?

[@Xiaoxiaoxiaomao]

👍🏻

[@waleedrafi1509]

Waiting for a video on backpropagation in CNN

[@CodingLane]

Okay... I will try to upload it sooner.

[@nivethikav1003]

How to calculate bias and weight

[@johncrouse6478]

bhai mza hi aa gya series mei ab to lgta topper ki gemd mei hi faadega lol.......

[@he_maxed]

Bro why we need ReLU and Bias?

[@waleedaiad3411]

How can i khow how many hidden layer used in facenet?

[@maximeentsi2205]

I'm asking the same question but generally the answer is : we cannot predict how many hidden layers we need, so you've to test and see what features your model is going to detect

[@waleedaiad3411]

@@maximeentsi2205 is bottleneck layer size mean the number of hidden layer?

[@waleedaiad3411]

@@maximeentsi2205 can i send to you on whatsapp on facebook or any things else for talk about this topic?

[@CodingLane]

General idea is, if you think, your data has more complicated information, then use more number of hidden layers. You need to test your model by training and checking the accuracy, and chose the number of layers that gives highest accuracy.

[@ayushmanbanikya4948]

What about CNN architecture ? U haven't explained about Resnet vgg n all

[@sonicdash793]

plz urdu maa bana do koi playlist

[@CodingLane]

Hi, I don’t speak urdu 😅. But thanks for the suggestion 🙂

[@nenunene5797]

Small correction: You are not going to any beauty contest..For God sake please stop advertising.

[@ares7785]

Bro please add your instagram I'd in description on upcoming video

[@CodingLane]

Hello... here is my insta handle @jaiminpatel_009