Image Recognition for Fashion with Machine Learning

Can a computer automatically detect pictures of shirts, pants, dresses, and sneakers? It turns out that accurately classifying images of fashion items is surprisingly straight-forward to do, given quality training data to start from. Supervised learning, in particular for classification, is a popular topic amongst artificial intelligence and machine learning enthusiasts. It's common for developers to utilize a well known and easy to process dataset for their first attempts at using supervised learning. The MNIST dataset is an example of such a source, providing thousands of examples of handwritten digits that can be used for supervised learning with your machine learning algorithms. I've previously written about classifying handwritten digits with the MNIST data-set, achieving accuracies of 99% on the training set and 97% on the test set. Data sets such as these are a convenient way to hone your skills and machine learning model development with a tried and trusted data source. It's important to keep in mind that a good data set has several features in common.