Fully Connected Layer in CNN

In this video, we will understand what is Fully Connected Layer in CNN and what is the purpose of using Fully Connected Layer.
Fully Connected Layer in CNN is an important part of CNN architecture. The purpose of fully connected layer is to classify the detected features into a category and also to learn to associate detected features to a particular label.
Fully Connected Layer is just like an artificial Neural Network, where every neuron in it, is connected to every other neuron in the next layer and the previous layer.
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Timestamp:
0:00 Intro
1:59 What is Fully Connected Layer in CNN
3:37 Summary
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Follow my entire playlist on Convolutional Neural Network (CNN) :
📕 CNN Playlist: www.youtube.com/watch?v=E5Z7F...
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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✔ Complete Neural Network Playlist: • What is CNN in deep le...
✔ Complete Logistic Regression Playlist: • Logistic Regression Ma...
✔ Complete Linear Regression Playlist: • What is Linear Regress...
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[@DeepakPanwar-gv7rk]

This series is quite good for understanding how CNN works thanks a lot man

[@biswajit-k]

Nice and easy to understand explanation. Thanks!

[@dikshasancheti6845]

Great explanation in a very simple way

[@rasyidabdillah881]

Your video is so so helpful for me to understand about CNN. Kidos for you 🎉🎊

[@bhushanambhore8378]

Crystal clear explaination

[@rohitrannavre9382]

You always hit the nail brother! I like your way of explanation.

[@CodingLane]

Thank you! Glad to help!

[@jtkklb]

Explained very well

[@warriorspartan1697]

Very simple and beautiful explanation. Thank you very much Sir.

[@CodingLane]

Welcome!

[@javaria_Ibrahim]

Thanks

[@sarthakjoshi21]

bro is there any major difference between CNN model vs full connected Cnn model if yes then what ? pls tell

[@DRTERRORGAMING]

Can you please make a video series of Audio Classification using CNN. 🙏

[@venompubgmobile7218]

thank you sir for making this all for free

[@CodingLane]

Your most welcome!

[@myquestforknowledge]

nice explanation. CNN layers do complex jobs of finding edges through filters. So CNN + flatten layer + ANN gives output.

[@blackyogurt]

simple and great ! thnaks

[@CodingLane]

Welcome 🤗

[@waleedaiad3411]

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

[@srinidhic4735]

This is so helpful

[@CodingLane]

Glad to help

[@-FitriNailahAnwar]

Please turn on the subtitle, so far thats clear vid, goood job sirrr 🙏🏻

[@CodingLane]

Sorry for the inconvenience. RUclips is facing error to add subtitles for this video. Glad you found it helpful.

[@user-db6fu1hw5x]

On what basis the Fully connected neurons reduce in each stage

[@chaimaef395]

very useful thanks

[@CodingLane]

Welcome!

[@malikhamza9286]

Amazing Video

[@CodingLane]

Thank You!

[@khaleddawoud363]

thank you

[@CodingLane]

Your welcome!

[@anefuoche1053]

on point

[@CodingLane]

Thank you so much!

[@adarshvadapalli]

@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.

[@ranveervaghela7030]

Wow explanation

[@CodingLane]

Thank you 😄

[@ramyajayaram4140]

Kindly clear my doubt.......Fully connected layer and fully conventional network are same

[@kirolloseisa]

Please add the other subtitles

[@sam-mv6vj]

Bro you said you will do detailed EDA and preprocessing in multiple linear regression but you didn't ,can you please make video on that ,and when you explain new topic do from basic like theory and in implementation preprocessing and all that will be really helpful Thanks

[@CodingLane]

Hello Sam! I will be uploading that video, but it will take some time.
I have already created a written tutorial article on the topic you desire.
Here is the link for that: www.kaggle.com/jaimin09/simplest-way-to-reach-top-25-from-bottom-25
In this tutorial, I have explained the basics of data preprocessing and how to preprocess data for house price prediction.
Please do check it out. It's an article, but I have tried to explain everything properly.
I will create a video of the same in the future.
But until then, I hope this article can help you.
Let me know for anything else!

[@sam-mv6vj]

@@CodingLane thanks

[@walidhamouich486]

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[@robertadiaferia6906]

Good video, add subtitle

[@CodingLane]

Hi Roberta… thanks for making me aware of the subtitles. Subtitles are somehow not added to this video. I will try to fix it!

[@yeeter269]

yo, don't disable subtitles or transcription

[@CodingLane]

Hi, thanks for the suggestion… RUclips is facing issues adding subtitles on this video… I will try to resolve.

[@manimeghana1612]

In binary classification we will be having 2 categories know..then why does the number of neurons in output layer will be 1

[@amazingsoyuz873]

Sigmoid activation on 1 neuron. It converts the value to a value between 0 and 1. If value < 0.5 then it's category 1, if greater then it's category 2

[@srx2106]

can you make a k mean from scratch video?

[@CodingLane]

Yes... I will make it... but it will take some time

[@chamanthipyneni7827]

How many layers does a cnn need to have for 4 class labels?

[@hemantnagardhane1497]

Sir please make vedios are n Rnn

[@CodingLane]

Sure.. will make video playlist on that as well!

[@CodingLane]

RNN Videos are out Hemant! Hope you find them valuable.