In this project, I build a convolutional neural network (CNN) with Tensorflow to classify images from the CIFAR-10 dataset, which consists of 60000 32x32 color images in 10 classes of vehicles and animals. An accuracy of 67% is achieved.

This is an adaptation of a project carried out in the context of the Deep Learning Nanodegree Foundation by Udacity.