Convolutional Neural Network (CNN) Implementation in Deep Learning

In this video, we are going to see the implementation of CNN using Python. CNN stands for Convolution Neural Network, it is a deep learning neural network for processing structure and class of artificial neural network (ANN) and it is used to apply to analyze visual imagery.

It can be used for various applications like Medical imaging, Audio Processing, Stop sign detection etc.

Here we are going to use a TensorFlow. An open-source software library is TensorFlow. TensorFlow was initially created by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organisation for the purposes of conducting deep learning and machine learning research.

Layers of CNN:
1) Input layer
2) The convolutional layer
3) The pooling layer
4) The ReLU correction layer
5) The fully-connected layer
6) Output layer

CNN in tensor flow:  https://www.geeksforgeeks.org/convolutional-neural-network-cnn-in-tensorflow/