This paper discusses on the fruits classification for which the data is collected from the dataset called Fruits_360. Using this data, training of a neural network which will identify the fruit. Using the deep learning and image processing concepts form a neural networking system. The proposed work uses convolution neural networks in building the model and also used ResNet to get the results of image classification from deep learning concept. To meet the resource requirement for the proposed work, it uses Google cloud vision API which gives us the required GPU to proceed with the process of analyzing the data from the image and also discussed the in depth of how image classification is done using deep learning concepts. Here, in building a deep learning model, which classifies the given image into any of these nine categories: Apple, Avocado, Banana, Cherry, Cocos, Kiwi, Mango, Orange, Lemon. This model can also be implemented into mobile version. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.