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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. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Timestamp: 0:00 Intro 1:59 What is Fully Connected Layer in CNN 3:37 Summary ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow my entire playlist on Convolutional Neural Network (CNN) : 📕 CNN Playlist: https://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. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ✔ Complete Neural Network Playlist:    • What is CNN in deep learning? Convolu...   ✔ Complete Logistic Regression Playlist:    • Logistic Regression Machine Learning ...   ✔ Complete Linear Regression Playlist:    • What is Linear Regression in Machine ...   ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ If you want to ride on the Lane of Machine Learning, then Subscribe ▶ to my channel here:https://www.youtube.com/channel/UCJFA