The Value of Semi-Supervised Machine Learning

Your boss hands you a pile of a 100,000 unlabeled images and asks you to categorize whether they are sandals, pants, boots, etc. So now you have a massive set of unlabeled data and you need labels. Lots of companies are swimming with data, whether its transactional, IoT sensors, security logs, images, voice, or more, and its all unlabeled. With so little labeled data, it is a tedious and slow process for data scientists to build machine learning models in most all enterprises. Take Google's street view data. Gebru had to figure out how to label cars in 50 million images with very little labeled data.