A Comparative Study of Classification Algorithms Over Images Using Machine Learning and TensorFlow

In today's world of technology, the fields of image processing are the trending research field of image classification aimed at image analysis. Image classification focuses on the labeling of images corresponding to the respective class label. Many researchers have applied several classification methods for image classification. The fundamental aim of classification is to achieve maximum precision, concentrating on the study of few classification algorithms and the comparison of classification accuracies. A comparative analysis of machine learning algorithms such as artificial neural networks and convolutionary neural networks applied to image data downloaded from an open-source data repository called Kaggle was carried out in this article. The implementation of the algorithms in this paper has been carried out using TensorFlow. It is evident from the experimental results that the classification is achieved better through convolutional neural networks.