Image Classification using Deep Learning (original) (raw)

Deep Learning aims to work on complex data and achieve accuracy. It works on AI-based domains like Natural Language Processing and Computer vision[1]. In deep learning, the computer model learns to perform classification of task from images, text or sound. Image classification is the task of extracting essential features from given input image that are required to predict the correct classification. The objective is to build a Convolution Neural Network model that can correctly predict and classify the input image as Dog or Cat. The classification is done by extracting specific features of the input image. The CNN Model consists of various layers like Convolution layer, ReLU layer, Pooling layer, etc. The model is trained well with training data. At last, the CNN model is tested for accuracy in image classification with the help of some test images.