Convolutional Neural Network (CNN): Introduction and Implementation
#cnn #neuralnetworks #deeplearning #machinelearning #ai
In this video, I introduced convolutional neural network (CNN) and showed it’s implementation. CNN is a type of deep learning algorithm mainly used for processing and analyzing image data by automatically learning spatial features through backpropagation. It consists of layers such as convolutional layers, pooling layers, and fully connected layers, enabling it to efficiently recognize patterns and objects in images and videos.
Github repository for the code: https://github.com/manishasirsat/cnn-implementation
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Chapters (16)
Intro
4:21
input layer
4:50
convolutional layer
5:55
Filter/kernel
9:35
Stride
13:18
Padding
14:32
activation function
17:32
pooling layer
19:51
flattening layer
20:40
fully connected layer
21:41
output layer
23:58
backpropogation
25:25
Loss function
26:25
optimizer
27:05
CNN hyper-parameters
28:59
CNN implementation
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