# Understanding convolutional neural network(CNN)

In the following tutorial, we will be understanding about the **convolutional neural network (CNN)** which is the most important tool in machine learning and deep learning, in addition, to provide a good understanding we will providing good visualization.

Next Part of this tutorial:

## Introduction to **convolutional neural network – CNN**

**convolutional neural network(CNN)** have large applications in image and video recognition, classification, recommender systems, and **natural language processing** also known as NLP. In this tutorial, the example that I will take is related to Computer Vision. However, the basic concept remains the same and can be applied to any other situation.

let’s take the example of a car.

### Convolutional Neural Network – CNN with example

To recognize a car by a deep learning model we need to follow the following steps.

- Input layer
- Convolutional layer
- Max Pooling
- Flattening
- Fully connected layer
- Output layer

as show above we have to put our image in the input layer then it will be converted into a convolutional layer which will take result in next step that is max pooling which is finally connected to an artificial neural network (ANN) for more about please refer to (Understanding Artificial Neural network (ANN)) which gives the prediction value of the image which we have used as input layer.

for more detail.

let’s assume the above example. car

First, the image will be converted into matrix form which each box representing RGB value of the corresponding box. As shown below.

then we will apply various which will be explained in the next tutorial.

**Next Part of this tutorial:**

#### Conclusion of CNN Understanding with an example:

hence we have covered the following part

- what is the convolutional neural network(CNN)?
- a brief introduction to the convolutional neural network(CNN)
- various step need for building a simple convolutional neural network(CNN)
- converting an image into the input layer(preprocessing)

I hope you enjoyed this tutorial, we will be covering more about the convolutional neural network(CNN) in the next tutorial until then enjoy learning.

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