Image Classification using Neural Networks

Abstract

As the world is currently engaged with Internet for all its work and will continue to do so in future . Now the mundane works of the users are seeking the help of Artificial Intelligence for its effectiveness and for its learning. Going ahead, AI algorithms will be fused into an ever increasing number of ordinary applications. For instance, you should need to incorporate a picture classifier in a Smartphone application. To do this, you'd utilize a deep learning model prepared on countless pictures as a feature of the general application architecture. A huge piece of programming improvement later on will utilize these sorts of models as common parts of uses. In this project, we'll train a image classifier to classify distinctive types of flowers. You can imagine utilizing something like this in a phone application that reveals to you the name of the flower your camera is taking a look at. In practice, you'd train this classifier, at that point send out it for use in your application. We'll be utilizing this dataset of around 100 flower categories. When we will finish this undertaking, we'll have an application that can be trained on any arrangement of marked pictures. Here your system will find out about flowers and end up as an command line application. In any case, the use of the task is altogether subject to the client.