Understand CNN Basics with a Keras Example in Python

In this article, we will try to implement the basic CNN model with the Keras framework. The benefit of the convolutional neural network is that it reduces or minimizes the dimension and parameters of images by retaining maximum information so that the training process becomes fast and takes less computation power. We will try to implement the code in google colab with a step-by-step process. Why we are using CNN? The main concern of using the convolutional neural network is for the images that previous algorithms are not so much suitable for bulk images dataset and retaining the image information.