In Artifical Intelligence, Convolutional Neural networks deal with every part that allows computers to see, To have the visual capability like Humans. In other words convnets are used to recognize images by transforming the original image through layers to a class scores.

Yann Lucn is the father of CNN. He was the one of the first persons who worked and devploed CNN. He is also an student of Geoffrey Hinton who is the Father of modern artifical intelligence.

This CNN was also inspired by the human visual cortex working. Like Every time we see something, a series of layers of neurons gets activated, and each layer will detect a set of features such as lines, edges. The high level of layers will detect more complex features in order to recognize what we saw.

In this repository we will learn:

1. What are CNN?
2. Convolution Operation
3. Pooling
4. Normalization
5. Flattening
6. Regularization
7. Cifar10 dataset Image classification
8. Building a Neural Network with TensorFlow

• In the "Part1" I have explained a general overview of cnn and it's working architecture. In the "Part2" I have done a image classification using tensorflow on cifar10 image dataset.

Note: Most of the images I used in this project are created by myself and also I mentioned the source of the Pics which I didn't make.