Building an Image Classifier in Tensorflow

This article guides on building a basic image classification model using Python and TensorFlow for processing images sent by members of an iOS app integrated with Nexmo In-App Messaging. The model is trained on the CIFAR-10 dataset, which contains 10 classes with 6000 images per class. After training the model, it is converted into Core ML format to facilitate its use in the iOS app. The article provides a step-by-step guide on building and deploying the model, including importing it into an Xcode project and integrating it into a Stitch Demo Application. The final accuracy of the model is 81%, with a loss of 0.7, indicating that it can classify images accurately but may have some errors in certain cases.