Fully Connected Layer in CNN
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- čas přidán 27. 07. 2024
- 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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This series is quite good for understanding how CNN works thanks a lot man
Nice and easy to understand explanation. Thanks!
Great explanation in a very simple way
Crystal clear explaination
Your video is so so helpful for me to understand about CNN. Kidos for you 🎉🎊
You always hit the nail brother! I like your way of explanation.
Thank you! Glad to help!
Explained very well
Very simple and beautiful explanation. Thank you very much Sir.
Welcome!
Can you please make a video series of Audio Classification using CNN. 🙏
Thanks
thank you sir for making this all for free
Your most welcome!
nice explanation. CNN layers do complex jobs of finding edges through filters. So CNN + flatten layer + ANN gives output.
simple and great ! thnaks
Welcome 🤗
This is so helpful
Glad to help
How can i khow how many hidden layer used in facenet?
Amazing Video
Thank You!
On what basis the Fully connected neurons reduce in each stage
very useful thanks
Welcome!
bro is there any major difference between CNN model vs full connected Cnn model if yes then what ? pls tell
Please add the other subtitles
thank you
Your welcome!
Please turn on the subtitle, so far thats clear vid, goood job sirrr 🙏🏻
Sorry for the inconvenience. CZcams is facing error to add subtitles for this video. Glad you found it helpful.
on point
Thank you so much!
Wow explanation
Thank you 😄
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
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!
@@CodingLane thanks
Kindly clear my doubt.......Fully connected layer and fully conventional network are same
Good video, add subtitle
Hi Roberta… thanks for making me aware of the subtitles. Subtitles are somehow not added to this video. I will try to fix it!
can you make a k mean from scratch video?
Yes... I will make it... but it will take some time
In binary classification we will be having 2 categories know..then why does the number of neurons in output layer will be 1
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
yo, don't disable subtitles or transcription
Hi, thanks for the suggestion… CZcams is facing issues adding subtitles on this video… I will try to resolve.
How many layers does a cnn need to have for 4 class labels?
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Sir please make vedios are n Rnn
Sure.. will make video playlist on that as well!
RNN Videos are out Hemant! Hope you find them valuable.